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Research Methodology – Types, Examples and writing Guide

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Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

• Provide an overview of the research problem and the need for a research methodology section
• Outline the main research questions and objectives

II. Research Design

• Explain the research design chosen and why it is appropriate for the research question(s) and objectives
• Discuss any alternative research designs considered and why they were not chosen
• Describe the research setting and participants (if applicable)

III. Data Collection Methods

• Describe the methods used to collect data (e.g., surveys, interviews, observations)
• Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

• Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
• Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or software used for data analysis

V. Ethical Considerations

• Discuss any ethical issues that may arise from the research and how they were addressed
• Explain how informed consent was obtained (if applicable)
• Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

• Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

• Summarize the key aspects of the research methodology section
• Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

• Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
• Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
• Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
• Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
• Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
• Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
• Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
• Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

• To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
• To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
• To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
• To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
• To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
• To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
• To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
• To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
• To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

• To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
• To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
• To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
• To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
• To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

• Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
• Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
• Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
• Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
• Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
• Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
• Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
• Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

About the author.

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• All About Thesis Methodology Flowcharts

Methodology flowchart thesis illustrations show how you plan to do your research. They help you understand your research goals and guide you in choosing the right questions, selecting samples, collecting data, and analyzing it.

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When writing a thesis, dissertation, or academic article, you need to present information in a structured way. To do this, researchers use different methods and approaches to gather and analyze data. The methodology section of a thesis is important because it explains what you did and how you conducted your research. This helps readers evaluate the accuracy and trustworthiness of your work.

Most researchers employ methodology flowchart thesis presentations to strategize, structure, portray, and conceptualize their research methodologies. This article demonstrates the importance of thesis methodology flowcharts through real-life thesis flow chart examples and a practical way to construct them.

In this article

• Importance of Thesis Research Methodology Flowcharts
• EdrawMax- A One-Stop Solution to Thesis Methodology Flowchart Designing Needs!
• How to Craft a Detailed Thesis Methodology Flowchart Using EdrawMax?

Part I: Importance of Thesis Research Methodology Flowcharts

The research thesis methodology flowcharts show how you will tackle your research questions, making your research more successful. Creating a thesis flowchart involves studying the theories and ideas that guide the procedures in your field and organizing your activities in a step-by-step order.

Research methodology flowcharts are very important because they provide a clear plan that helps researchers stay focused and makes the process efficient and manageable. It ensures that your conclusions are based on scientific principles and gives your research credibility.

Part II: EdrawMax- A One-Stop Solution to Thesis Methodology Flowchart Designing Needs!

Creating a structure for your dissertation takes a lot of time. You need to organize your ideas and have strong supporting details. If you don't arrange things in order, your ideas can become confused and unclear. To avoid this, you need a modern diagramming tool that can help you save time and focus on writing your dissertation.

EdrawMax helps you bring your ideas to life when designing thesis flowcharts. It has many useful features like a wide range of symbols, the ability to create multiple pages, helpful alignment tools, easy customization options, and various ways to export your work. Whether you're a student, researcher, teacher, or anyone in education, EdrawMax is a complete solution for all your drawing needs.

Visual Illustration of a Thesis Methodology Flowchart

Consider this practical methodology flowchart thesis example to gain insights into how a well-structured thesis methodology flowchart seems:

When you conduct research, it's important to follow a step-by-step process to ensure accurate and reliable results. This process involves discovering, collecting, evaluating, and presenting ideas in a specific order. By following this standardized procedure, your thesis will be reliable and won't have any incorrect findings. Here is the methodized step-by-step process to help you formulate your thesis research methodology:

Preliminary Strategizing

Before starting your research, it's important to plan ahead. This involves choosing the location, field, and community where you will conduct your research. It's also important to get permission from the community to conduct your research, as it's an ethical concern.

Next, you need to set a clear objective for your thesis and come up with a logical research question. You can do this by observing, studying, or analyzing a situation. Observations can be intentional, where you purposely observe a specific behavior in a community. Sometimes, research questions arise from analyzing current situations, like the coronavirus, pollution, or poverty in a certain town.

Data Collection

Collecting data is an important step in research. It involves observing or measuring things in a systematic way. Before you start collecting data, you need to clearly define your goals. You can do this by explaining the problem you want to address. For example, you might collect data on bomb blast victims or people with aggressive behaviors.

There are two types of data: primary and secondary data. Primary data is information that you collect directly from original sources. Secondary data, on the other hand, is information that has already been gathered or processed by someone else.

Data Processing

After collecting data, the next step is to decide how to process and analyze it. Data processing is when you take the collected data and turn it into useful information that can be used by others. This information can help support or disprove theories, make decisions, or bring about positive changes in a community.

To choose the right data processing method, consider the nature and type of your research and think about your thesis research question. It's important not to get too specific at this stage and avoid discussing any results. Focus on finding a suitable technique that will help you process and analyze your data effectively.

Data Analysis

Researchers use data analysis to make sense of their research findings by organizing, combining, summarizing, and categorizing the data. This helps them identify patterns and themes in the information they have collected.

In the thesis methodology flowchart example mentioned above, the data analysis techniques used are lean and six sigma concepts. These methods follow a series of steps, including defining, measuring, analyzing, categorizing, and improving the data to make it more meaningful and valuable.

Evaluation Phase

Data evaluation is a way to check if data is trustworthy, thorough, and consistent. It involves comparing data with specific goals, finding any missing information, and discovering trends, patterns, and connections. Another name for data evaluation is data mining because it uses statistical analysis to uncover valuable insights and generate better information.

Report Writing

Once you have finished your research, it's time to organize and present the information you have gathered. Report writing involves putting all the information together, drawing conclusions based on your findings, and providing recommendations based on the results. It's important to consider who will be reading your report, as the audience plays a significant role in how you present your information.

Part III: How to Craft a Detailed Thesis Methodology Flowchart Using EdrawMax?

EdrawMax is a user-friendly and affordable tool that helps people create detailed diagrams quickly. It's accessible to both small and medium-sized users, making it easy for everyone to make complex diagrams in just a few minutes. Let's see how you can use EdrawMax to create a fantastic flowchart for organizing your thesis.

Download and launch "EdrawMax" on your device for thesis methodology flowchart creation.

Click the "New" tab in the left pane, hover over the "Basic Flowchart" tab, and click the "Create New" button.

Sketch the skeleton of your thesis methodology flowchart by drawing all the required shapes on the canvas at accurate locations.

Embed relevant information in each box to portray your details in exact sequence; you can also rescale the shapes to accommodate larger texts.

Join all the shapes to develop a flow in your thesis methodology flowchart; for this, navigate to the "Connector" tab in the "Home" menu.

You can also personalize the outlook of your thesis research methodology flowchart for enhanced understanding; to do so, navigate to the "Design" tab and apply your desired changes.

To customize an individual item or multiple items simultaneously, select those items and perform your preferred modification.

Click the "Export" option at the top and choose your desired format to save your research thesis methodology flowchart.

Benefits of Using EdrawMax for Thesis Methodology Flowchart Designing

Before using a diagramming application, it's important to consider its features, price, compatibility, and other important factors. Doing thorough research on these aspects will help you make an informed decision and avoid the inconvenience of switching between multiple tools because they don't have the right features for your needs.

EdrawMax is an excellent platform for designing methodology flow chart thesis projects because it offers a wide range of tools that suit everyone's needs. We have listed several reasons why EdrawMax is the best choice for creating your academic diagrams.

• EdrawMax has a Templates Community where you can find ready-made templates to save you the trouble of starting from scratch. It also has a variety of symbols libraries to create different types of flowcharts, making it more fun and expressive.
• With EdrawMax, you can add multiple pages to your thesis flowchart project, keeping your ideas organized and avoiding complexity. You can also enhance your flowcharts by adding pictures, hyperlinks, charts, tables, icons, and other elements to make them insightful and expressive.
• The user interface of EdrawMax is easy to use, with a quick toolbar that allows you to customize shapes and text with just one click. Even the free version of EdrawMax offers customization options like fill and border color, border style, width, rescaling, background type, connector type, and font customization.
• EdrawMax also supports real-time collaboration, which is helpful when you need to discuss and refine your methodology flowchart with your research supervisor. Additionally, you can export your methodology flowchart thesis file in various formats such as PNG, JPG, PDF, SVG, and Visio.
• Overall, EdrawMax provides a user-friendly and versatile platform for creating and customizing methodology flowcharts for your thesis.

Writing a thesis requires careful attention to analyzing and presenting research findings. The methodology you choose for your dissertation plays a crucial role in how you collect data, analyze it, and present your results. Whether you're conducting qualitative or quantitative research, the methodology you use has a significant impact on your entire dissertation.

To make your research more organized, you can create a thesis methodology flowchart . This flowchart helps you outline and visualize the step-by-step process of your research, from selecting techniques and approaches to analyzing data and presenting results. This article offers a detailed guide on how to create a practical and visually appealing thesis methodology flowchart to enhance your research process.

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What Is Research Methodology? A Plain-Language Explanation & Definition (With Examples)

By Derek Jansen (MBA)  and Kerryn Warren (PhD) | June 2020 (Last updated April 2023)

If you’re new to formal academic research, it’s quite likely that you’re feeling a little overwhelmed by all the technical lingo that gets thrown around. And who could blame you – “research methodology”, “research methods”, “sampling strategies”… it all seems never-ending!

In this post, we’ll demystify the landscape with plain-language explanations and loads of examples (including easy-to-follow videos), so that you can approach your dissertation, thesis or research project with confidence. Let’s get started.

Research Methodology 101

• What exactly research methodology means
• What qualitative , quantitative and mixed methods are
• What sampling strategy is
• What data collection methods are
• What data analysis methods are
• How to choose your research methodology
• Example of a research methodology

What is research methodology?

Research methodology simply refers to the practical “how” of a research study. More specifically, it’s about how  a researcher  systematically designs a study  to ensure valid and reliable results that address the research aims, objectives and research questions . Specifically, how the researcher went about deciding:

• What type of data to collect (e.g., qualitative or quantitative data )
• Who  to collect it from (i.e., the sampling strategy )
• How to  collect  it (i.e., the data collection method )
• How to  analyse  it (i.e., the data analysis methods )

Within any formal piece of academic research (be it a dissertation, thesis or journal article), you’ll find a research methodology chapter or section which covers the aspects mentioned above. Importantly, a good methodology chapter explains not just   what methodological choices were made, but also explains  why they were made. In other words, the methodology chapter should justify  the design choices, by showing that the chosen methods and techniques are the best fit for the research aims, objectives and research questions. 

So, it’s the same as research design?

Not quite. As we mentioned, research methodology refers to the collection of practical decisions regarding what data you’ll collect, from who, how you’ll collect it and how you’ll analyse it. Research design, on the other hand, is more about the overall strategy you’ll adopt in your study. For example, whether you’ll use an experimental design in which you manipulate one variable while controlling others. You can learn more about research design and the various design types here .

Need a helping hand?

What are qualitative, quantitative and mixed-methods?

Qualitative, quantitative and mixed-methods are different types of methodological approaches, distinguished by their focus on words , numbers or both . This is a bit of an oversimplification, but its a good starting point for understanding.

Let’s take a closer look.

Qualitative research refers to research which focuses on collecting and analysing words (written or spoken) and textual or visual data, whereas quantitative research focuses on measurement and testing using numerical data . Qualitative analysis can also focus on other “softer” data points, such as body language or visual elements.

It’s quite common for a qualitative methodology to be used when the research aims and research questions are exploratory  in nature. For example, a qualitative methodology might be used to understand peoples’ perceptions about an event that took place, or a political candidate running for president. 

Contrasted to this, a quantitative methodology is typically used when the research aims and research questions are confirmatory  in nature. For example, a quantitative methodology might be used to measure the relationship between two variables (e.g. personality type and likelihood to commit a crime) or to test a set of hypotheses .

As you’ve probably guessed, the mixed-method methodology attempts to combine the best of both qualitative and quantitative methodologies to integrate perspectives and create a rich picture. If you’d like to learn more about these three methodological approaches, be sure to watch our explainer video below.

What is sampling strategy?

Simply put, sampling is about deciding who (or where) you’re going to collect your data from . Why does this matter? Well, generally it’s not possible to collect data from every single person in your group of interest (this is called the “population”), so you’ll need to engage a smaller portion of that group that’s accessible and manageable (this is called the “sample”).

How you go about selecting the sample (i.e., your sampling strategy) will have a major impact on your study.  There are many different sampling methods  you can choose from, but the two overarching categories are probability   sampling and  non-probability   sampling .

Probability sampling  involves using a completely random sample from the group of people you’re interested in. This is comparable to throwing the names all potential participants into a hat, shaking it up, and picking out the “winners”. By using a completely random sample, you’ll minimise the risk of selection bias and the results of your study will be more generalisable  to the entire population. 

Non-probability sampling , on the other hand,  doesn’t use a random sample . For example, it might involve using a convenience sample, which means you’d only interview or survey people that you have access to (perhaps your friends, family or work colleagues), rather than a truly random sample. With non-probability sampling, the results are typically not generalisable .

To learn more about sampling methods, be sure to check out the video below.

What are data collection methods?

As the name suggests, data collection methods simply refers to the way in which you go about collecting the data for your study. Some of the most common data collection methods include:

• Interviews (which can be unstructured, semi-structured or structured)
• Focus groups and group interviews
• Surveys (online or physical surveys)
• Observations (watching and recording activities)
• Biophysical measurements (e.g., blood pressure, heart rate, etc.)
• Documents and records (e.g., financial reports, court records, etc.)

The choice of which data collection method to use depends on your overall research aims and research questions , as well as practicalities and resource constraints. For example, if your research is exploratory in nature, qualitative methods such as interviews and focus groups would likely be a good fit. Conversely, if your research aims to measure specific variables or test hypotheses, large-scale surveys that produce large volumes of numerical data would likely be a better fit.

What are data analysis methods?

Data analysis methods refer to the methods and techniques that you’ll use to make sense of your data. These can be grouped according to whether the research is qualitative  (words-based) or quantitative (numbers-based).

Popular data analysis methods in qualitative research include:

• Qualitative content analysis
• Thematic analysis
• Discourse analysis
• Narrative analysis
• Interpretative phenomenological analysis (IPA)
• Visual analysis (of photographs, videos, art, etc.)

Qualitative data analysis all begins with data coding , after which an analysis method is applied. In some cases, more than one analysis method is used, depending on the research aims and research questions . In the video below, we explore some  common qualitative analysis methods, along with practical examples.  

Moving on to the quantitative side of things, popular data analysis methods in this type of research include:

• Descriptive statistics (e.g. means, medians, modes )
• Inferential statistics (e.g. correlation, regression, structural equation modelling)

Again, the choice of which data collection method to use depends on your overall research aims and objectives , as well as practicalities and resource constraints. In the video below, we explain some core concepts central to quantitative analysis.

How do I choose a research methodology?

As you’ve probably picked up by now, your research aims and objectives have a major influence on the research methodology . So, the starting point for developing your research methodology is to take a step back and look at the big picture of your research, before you make methodology decisions. The first question you need to ask yourself is whether your research is exploratory or confirmatory in nature.

If your research aims and objectives are primarily exploratory in nature, your research will likely be qualitative and therefore you might consider qualitative data collection methods (e.g. interviews) and analysis methods (e.g. qualitative content analysis). 

Conversely, if your research aims and objective are looking to measure or test something (i.e. they’re confirmatory), then your research will quite likely be quantitative in nature, and you might consider quantitative data collection methods (e.g. surveys) and analyses (e.g. statistical analysis).

Designing your research and working out your methodology is a large topic, which we cover extensively on the blog . For now, however, the key takeaway is that you should always start with your research aims, objectives and research questions (the golden thread). Every methodological choice you make needs align with those three components. 

Example of a research methodology chapter

In the video below, we provide a detailed walkthrough of a research methodology from an actual dissertation, as well as an overview of our free methodology template .

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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199 Comments

Thank you for this simple yet comprehensive and easy to digest presentation. God Bless!

You’re most welcome, Leo. Best of luck with your research!

I found it very useful. many thanks

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Thank u more

Thank you, your explanation is simple and very helpful.

Very educative a.nd exciting platform. A bigger thank you and I’ll like to always be with you

That’s the best analysis

So simple yet so insightful. Thank you.

This really easy to read as it is self-explanatory. Very much appreciated…

Thanks for this. It’s so helpful and explicit. For those elements highlighted in orange, they were good sources of referrals for concepts I didn’t understand. A million thanks for this.

Good morning, I have been reading your research lessons through out a period of times. They are important, impressive and clear. Want to subscribe and be and be active with you.

Thankyou So much Sir Derek…

Good morning thanks so much for the on line lectures am a student of university of Makeni.select a research topic and deliberate on it so that we’ll continue to understand more.sorry that’s a suggestion.

Beautiful presentation. I love it.

please provide a research mehodology example for zoology

It’s very educative and well explained

Thanks for the concise and informative data.

This is really good for students to be safe and well understand that research is all about

Thank you so much Derek sir🖤🙏🤗

Very simple and reliable

This is really helpful. Thanks alot. God bless you.

very useful, Thank you very much..

thanks a lot its really useful

in a nutshell..thank you!

Thanks for updating my understanding on this aspect of my Thesis writing.

thank you so much my through this video am competently going to do a good job my thesis

Thanks a lot. Very simple to understand. I appreciate 🙏

Very simple but yet insightful Thank you

This has been an eye opening experience. Thank you grad coach team.

Very useful message for research scholars

Really very helpful thank you

yes you are right and i’m left

Research methodology with a simplest way i have never seen before this article.

wow thank u so much

Good morning thanks so much for the on line lectures am a student of university of Makeni.select a research topic and deliberate on is so that we will continue to understand more.sorry that’s a suggestion.

Very precise and informative.

Thanks for simplifying these terms for us, really appreciate it.

Thanks this has really helped me. It is very easy to understand.

I found the notes and the presentation assisting and opening my understanding on research methodology

Good presentation

Im so glad you clarified my misconceptions. Im now ready to fry my onions. Thank you so much. God bless

Thank you a lot.

thanks for the easy way of learning and desirable presentation.

Thanks a lot. I am inspired

Well written

I am writing a APA Format paper . I using questionnaire with 120 STDs teacher for my participant. Can you write me mthology for this research. Send it through email sent. Just need a sample as an example please. My topic is ” impacts of overcrowding on students learning

Thanks for your comment.

We can’t write your methodology for you. If you’re looking for samples, you should be able to find some sample methodologies on Google. Alternatively, you can download some previous dissertations from a dissertation directory and have a look at the methodology chapters therein.

All the best with your research.

Thank you so much for this!! God Bless

Thank you. Explicit explanation

Thank you, Derek and Kerryn, for making this simple to understand. I’m currently at the inception stage of my research.

Thnks a lot , this was very usefull on my assignment

excellent explanation

I’m currently working on my master’s thesis, thanks for this! I’m certain that I will use Qualitative methodology.

Thanks a lot for this concise piece, it was quite relieving and helpful. God bless you BIG…

I am currently doing my dissertation proposal and I am sure that I will do quantitative research. Thank you very much it was extremely helpful.

Very interesting and informative yet I would like to know about examples of Research Questions as well, if possible.

I’m about to submit a research presentation, I have come to understand from your simplification on understanding research methodology. My research will be mixed methodology, qualitative as well as quantitative. So aim and objective of mixed method would be both exploratory and confirmatory. Thanks you very much for your guidance.

OMG thanks for that, you’re a life saver. You covered all the points I needed. Thank you so much ❤️ ❤️ ❤️

Thank you immensely for this simple, easy to comprehend explanation of data collection methods. I have been stuck here for months 😩. Glad I found your piece. Super insightful.

I’m going to write synopsis which will be quantitative research method and I don’t know how to frame my topic, can I kindly get some ideas..

Thanks for this, I was really struggling.

This was really informative I was struggling but this helped me.

Thanks a lot for this information, simple and straightforward. I’m a last year student from the University of South Africa UNISA South Africa.

its very much informative and understandable. I have enlightened.

An interesting nice exploration of a topic.

Thank you. Accurate and simple🥰

This article was really helpful, it helped me understanding the basic concepts of the topic Research Methodology. The examples were very clear, and easy to understand. I would like to visit this website again. Thank you so much for such a great explanation of the subject.

Thanks dude

Thank you Doctor Derek for this wonderful piece, please help to provide your details for reference purpose. God bless.

Many compliments to you

Great work , thank you very much for the simple explanation

Thank you. I had to give a presentation on this topic. I have looked everywhere on the internet but this is the best and simple explanation.

thank you, its very informative.

Well explained. Now I know my research methodology will be qualitative and exploratory. Thank you so much, keep up the good work

Well explained, thank you very much.

This is good explanation, I have understood the different methods of research. Thanks a lot.

Great work…very well explanation

Thanks Derek. Kerryn was just fantastic!

Great to hear that, Hyacinth. Best of luck with your research!

Its a good templates very attractive and important to PhD students and lectuter

Thanks for the feedback, Matobela. Good luck with your research methodology.

Thank you. This is really helpful.

You’re very welcome, Elie. Good luck with your research methodology.

Well explained thanks

This is a very helpful site especially for young researchers at college. It provides sufficient information to guide students and equip them with the necessary foundation to ask any other questions aimed at deepening their understanding.

Thanks for the kind words, Edward. Good luck with your research!

Thank you. I have learned a lot.

Great to hear that, Ngwisa. Good luck with your research methodology!

Thank you for keeping your presentation simples and short and covering key information for research methodology. My key takeaway: Start with defining your research objective the other will depend on the aims of your research question.

My name is Zanele I would like to be assisted with my research , and the topic is shortage of nursing staff globally want are the causes , effects on health, patients and community and also globally

Thanks for making it simple and clear. It greatly helped in understanding research methodology. Regards.

This is well simplified and straight to the point

Thank you Dr

I was given an assignment to research 2 publications and describe their research methodology? I don’t know how to start this task can someone help me?

Sure. You’re welcome to book an initial consultation with one of our Research Coaches to discuss how we can assist – https://gradcoach.com/book/new/ .

Thanks a lot I am relieved of a heavy burden.keep up with the good work

I’m very much grateful Dr Derek. I’m planning to pursue one of the careers that really needs one to be very much eager to know. There’s a lot of research to do and everything, but since I’ve gotten this information I will use it to the best of my potential.

Thank you so much, words are not enough to explain how helpful this session has been for me!

Thanks this has thought me alot.

Very concise and helpful. Thanks a lot

Thank Derek. This is very helpful. Your step by step explanation has made it easier for me to understand different concepts. Now i can get on with my research.

I wish i had come across this sooner. So simple but yet insightful

really nice explanation thank you so much

I’m so grateful finding this site, it’s really helpful…….every term well explained and provide accurate understanding especially to student going into an in-depth research for the very first time, even though my lecturer already explained this topic to the class, I think I got the clear and efficient explanation here, much thanks to the author.

It is very helpful material

I would like to be assisted with my research topic : Literature Review and research methodologies. My topic is : what is the relationship between unemployment and economic growth?

Its really nice and good for us.

THANKS SO MUCH FOR EXPLANATION, ITS VERY CLEAR TO ME WHAT I WILL BE DOING FROM NOW .GREAT READS.

Short but sweet.Thank you

Informative article. Thanks for your detailed information.

I’m currently working on my Ph.D. thesis. Thanks a lot, Derek and Kerryn, Well-organized sequences, facilitate the readers’ following.

great article for someone who does not have any background can even understand

I am a bit confused about research design and methodology. Are they the same? If not, what are the differences and how are they related?

Thanks in advance.

concise and informative.

Thank you very much

How can we site this article is Harvard style?

Very well written piece that afforded better understanding of the concept. Thank you!

Am a new researcher trying to learn how best to write a research proposal. I find your article spot on and want to download the free template but finding difficulties. Can u kindly send it to my email, the free download entitled, “Free Download: Research Proposal Template (with Examples)”.

Thank too much

Thank you very much for your comprehensive explanation about research methodology so I like to thank you again for giving us such great things.

Good very well explained.Thanks for sharing it.

Thank u sir, it is really a good guideline.

so helpful thank you very much.

Thanks for the video it was very explanatory and detailed, easy to comprehend and follow up. please, keep it up the good work

It was very helpful, a well-written document with precise information.

how do i reference this?

MLA Jansen, Derek, and Kerryn Warren. “What (Exactly) Is Research Methodology?” Grad Coach, June 2021, gradcoach.com/what-is-research-methodology/.

APA Jansen, D., & Warren, K. (2021, June). What (Exactly) Is Research Methodology? Grad Coach. https://gradcoach.com/what-is-research-methodology/

Your explanation is easily understood. Thank you

Very help article. Now I can go my methodology chapter in my thesis with ease

I feel guided ,Thank you

This simplification is very helpful. It is simple but very educative, thanks ever so much

The write up is informative and educative. It is an academic intellectual representation that every good researcher can find useful. Thanks

Wow, this is wonderful long live.

Nice initiative

thank you the video was helpful to me.

Thank you very much for your simple and clear explanations I’m really satisfied by the way you did it By now, I think I can realize a very good article by following your fastidious indications May God bless you

Thanks very much, it was very concise and informational for a beginner like me to gain an insight into what i am about to undertake. I really appreciate.

very informative sir, it is amazing to understand the meaning of question hidden behind that, and simple language is used other than legislature to understand easily. stay happy.

This one is really amazing. All content in your youtube channel is a very helpful guide for doing research. Thanks, GradCoach.

research methodologies

Please send me more information concerning dissertation research.

Nice piece of knowledge shared….. #Thump_UP

This is amazing, it has said it all. Thanks to Gradcoach

This is wonderful,very elaborate and clear.I hope to reach out for your assistance in my research very soon.

This is the answer I am searching about…

realy thanks a lot

Thank you very much for this awesome, to the point and inclusive article.

Thank you very much I need validity and reliability explanation I have exams

Thank you for a well explained piece. This will help me going forward.

Very simple and well detailed Many thanks

This is so very simple yet so very effective and comprehensive. An Excellent piece of work.

I wish I saw this earlier on! Great insights for a beginner(researcher) like me. Thanks a mil!

Thank you very much, for such a simplified, clear and practical step by step both for academic students and general research work. Holistic, effective to use and easy to read step by step. One can easily apply the steps in practical terms and produce a quality document/up-to standard

Thanks for simplifying these terms for us, really appreciated.

Thanks for a great work. well understood .

This was very helpful. It was simple but profound and very easy to understand. Thank you so much!

Great and amazing research guidelines. Best site for learning research

hello sir/ma’am, i didn’t find yet that what type of research methodology i am using. because i am writing my report on CSR and collect all my data from websites and articles so which type of methodology i should write in dissertation report. please help me. i am from India.

how does this really work?

perfect content, thanks a lot

As a researcher, I commend you for the detailed and simplified information on the topic in question. I would like to remain in touch for the sharing of research ideas on other topics. Thank you

Impressive. Thank you, Grad Coach 😍

Thank you Grad Coach for this piece of information. I have at least learned about the different types of research methodologies.

Very useful content with easy way

Thank you very much for the presentation. I am an MPH student with the Adventist University of Africa. I have successfully completed my theory and starting on my research this July. My topic is “Factors associated with Dental Caries in (one District) in Botswana. I need help on how to go about this quantitative research

I am so grateful to run across something that was sooo helpful. I have been on my doctorate journey for quite some time. Your breakdown on methodology helped me to refresh my intent. Thank you.

thanks so much for this good lecture. student from university of science and technology, Wudil. Kano Nigeria.

It’s profound easy to understand I appreciate

Thanks a lot for sharing superb information in a detailed but concise manner. It was really helpful and helped a lot in getting into my own research methodology.

Comment * thanks very much

This was sooo helpful for me thank you so much i didn’t even know what i had to write thank you!

You’re most welcome 🙂

Simple and good. Very much helpful. Thank you so much.

This is very good work. I have benefited.

Thank you so much for sharing

This is powerful thank you so much guys

I am nkasa lizwi doing my research proposal on honors with the university of Walter Sisulu Komani I m on part 3 now can you assist me.my topic is: transitional challenges faced by educators in intermediate phase in the Alfred Nzo District.

Appreciate the presentation. Very useful step-by-step guidelines to follow.

I appreciate sir

wow! This is super insightful for me. Thank you!

Indeed this material is very helpful! Kudos writers/authors.

I want to say thank you very much, I got a lot of info and knowledge. Be blessed.

I want present a seminar paper on Optimisation of Deep learning-based models on vulnerability detection in digital transactions.

Need assistance

Dear Sir, I want to be assisted on my research on Sanitation and Water management in emergencies areas.

I am deeply grateful for the knowledge gained. I will be getting in touch shortly as I want to be assisted in my ongoing research.

The information shared is informative, crisp and clear. Kudos Team! And thanks a lot!

hello i want to study

Hello!! Grad coach teams. I am extremely happy in your tutorial or consultation. i am really benefited all material and briefing. Thank you very much for your generous helps. Please keep it up. If you add in your briefing, references for further reading, it will be very nice.

All I have to say is, thank u gyz.

Good, l thanks

thank you, it is very useful

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Research Process: 8 Steps in Research Process

The research process starts with identifying a research problem and conducting a literature review to understand the context. The researcher sets research questions, objectives, and hypotheses based on the research problem.

A research study design is formed to select a sample size and collect data after processing and analyzing the collected data and the research findings presented in a research report.

What is the Research Process?

There are a variety of approaches to research in any field of investigation, irrespective of whether it is applied research or basic research. Each research study will be unique in some ways because of the particular time, setting, environment, and place it is being undertaken.

Nevertheless, all research endeavors share a common goal of furthering our understanding of the problem, and thus, all traverse through certain primary stages, forming a process called the research process.

Understanding the research process is necessary to effectively carry out research and sequence the stages inherent in the process.

How Research Process Work?

Eight steps research process is, in essence, part and parcel of a research proposal. It is an outline of the commitment that you intend to follow in executing a research study.

A close examination of the above stages reveals that each of these stages, by and large, is dependent upon the others.

One cannot analyze data (step 7) unless he has collected data (step 6). One cannot write a report (step 8) unless he has collected and analyzed data (step 7).

Research then is a system of interdependent related stages. Violation of this sequence can cause irreparable harm to the study.

It is also true that several alternatives are available to the researcher during each stage stated above. A research process can be compared with a route map.

The map analogy is useful for the researcher because several alternatives exist at each stage of the research process.

Choosing the best alternative in terms of time constraints, money, and human resources in our research decision is our primary goal.

Before explaining the stages of the research process, we explain the term ‘iterative’ appearing within the oval-shaped diagram at the center of the schematic diagram.

The key to a successful research project ultimately lies in iteration: the process of returning again and again to the identification of the research problems, methodology, data collection, etc., which leads to new ideas, revisions, and improvements.

By discussing the research project with advisers and peers, one will often find that new research questions need to be added, variables to be omitted, added or redefined, and other changes to be made. As a proposed study is examined and reexamined from different perspectives, it may begin to transform and take a different shape.

This is expected and is an essential component of a good research study.

Besides, examining study methods and data collected from different viewpoints is important to ensure a comprehensive approach to the research question.

In conclusion, there is seldom any single strategy or formula for developing a successful research study, but it is essential to realize that the research process is cyclical and iterative.

What is the primary purpose of the research process?

The research process aims to identify a research problem, understand its context through a literature review, set research questions and objectives, design a research study, select a sample, collect data, analyze the data, and present the findings in a research report.

Why is the research design important in the research process?

The research design is the blueprint for fulfilling objectives and answering research questions. It specifies the methods and procedures for collecting, processing, and analyzing data, ensuring the study is structured and systematic.

8 Steps of Research Process

Identifying the research problem.

The first and foremost task in the entire process of scientific research is to identify a research problem .

A well-identified problem will lead the researcher to accomplish all-important phases of the research process, from setting objectives to selecting the research methodology .

But the core question is: whether all problems require research.

We have countless problems around us, but all we encounter do not qualify as research problems; thus, these do not need to be researched.

Keeping this point in mind, we must draw a line between research and non-research problems.

Intuitively, researchable problems are those that have a possibility of thorough verification investigation, which can be effected through the analysis and collection of data. In contrast, the non-research problems do not need to go through these processes.

Researchers need to identify both;

Non-Research Problems

Statement of the problem, justifying the problem, analyzing the problem.

A non-research problem does not require any research to arrive at a solution. Intuitively, a non-researchable problem consists of vague details and cannot be resolved through research.

It is a managerial or built-in problem that may be solved at the administrative or management level. The answer to any question raised in a non-research setting is almost always obvious.

The cholera outbreak, for example, following a severe flood, is a common phenomenon in many communities. The reason for this is known. It is thus not a research problem.

Similarly, the reasons for the sudden rise in prices of many essential commodities following the announcement of the budget by the Finance Minister need no investigation. Hence it is not a problem that needs research.

How is a research problem different from a non-research problem?

A research problem is a perceived difficulty that requires thorough verification and investigation through data analysis and collection. In contrast, a non-research problem does not require research for a solution, as the answer is often obvious or already known.

Non-Research Problems Examples

A recent survey in town- A found that 1000 women were continuous users of contraceptive pills.

But last month’s service statistics indicate that none of these women were using contraceptive pills (Fisher et al. 1991:4).

The discrepancy is that ‘all 1000 women should have been using a pill, but none is doing so. The question is: why the discrepancy exists?

Well, the fact is, a monsoon flood has prevented all new supplies of pills from reaching town- A, and all old supplies have been exhausted. Thus, although the problem situation exists, the reason for the problem is already known.

Therefore, assuming all the facts are correct, there is no reason to research the factors associated with pill discontinuation among women. This is, thus, a non-research problem.

A pilot survey by University students revealed that in Rural Town-A, the goiter prevalence among school children is as high as 80%, while in the neighboring Rural Town-A, it is only 30%. Why is a discrepancy?

Upon inquiry, it was seen that some three years back, UNICEF launched a lipiodol injection program in the neighboring Rural Town-A.

This attempt acted as a preventive measure against the goiter. The reason for the discrepancy is known; hence, we do not consider the problem a research problem.

A hospital treated a large number of cholera cases with penicillin, but the treatment with penicillin was not found to be effective. Do we need research to know the reason?

Here again, there is one single reason that Vibrio cholera is not sensitive to penicillin; therefore, this is not the drug of choice for this disease.

In this case, too, as the reasons are known, it is unwise to undertake any study to find out why penicillin does not improve the condition of cholera patients. This is also a non-research problem.

In the tea marketing system, buying and selling tea starts with bidders. Blenders purchase open tea from the bidders. Over the years, marketing cost has been the highest for bidders and the lowest for blenders. What makes this difference?

The bidders pay exorbitantly higher transport costs, which constitute about 30% of their total cost.

Blenders have significantly fewer marketing functions involving transportation, so their marketing cost remains minimal.

Hence no research is needed to identify the factors that make this difference.

Here are some of the problems we frequently encounter, which may well be considered non-research problems:

• Rises in the price of warm clothes during winter;
• Preferring admission to public universities over private universities;
• Crisis of accommodations in sea resorts during summer
• Traffic jams in the city street after office hours;
• High sales in department stores after an offer of a discount.

Research Problem

In contrast to a non-research problem, a research problem is of primary concern to a researcher.

A research problem is a perceived difficulty, a feeling of discomfort, or a discrepancy between a common belief and reality.

As noted by Fisher et al. (1993), a problem will qualify as a potential research problem when the following three conditions exist:

• There should be a perceived discrepancy between “what it is” and “what it should have been.” This implies that there should be a difference between “what exists” and the “ideal or planned situation”;
• A question about “why” the discrepancy exists. This implies that the reason(s) for this discrepancy is unclear to the researcher (so that it makes sense to develop a research question); and
• There should be at least two possible answers or solutions to the questions or problems.

The third point is important. If there is only one possible and plausible answer to the question about the discrepancy, then a research situation does not exist.

It is a non-research problem that can be tackled at the managerial or administrative level.

Research Problem Examples

Research problem – example #1.

While visiting a rural area, the UNICEF team observed that some villages have female school attendance rates as high as 75%, while some have as low as 10%, although all villages should have a nearly equal attendance rate. What factors are associated with this discrepancy?

We may enumerate several reasons for this:

• Villages differ in their socio-economic background.
• In some villages, the Muslim population constitutes a large proportion of the total population. Religion might play a vital role.
• Schools are far away from some villages. The distance thus may make this difference.

Because there is more than one answer to the problem, it is considered a research problem, and a study can be undertaken to find a solution.

Research Problem – Example #2

The Government has been making all-out efforts to ensure a regular flow of credit in rural areas at a concession rate through liberal lending policy and establishing many bank branches in rural areas.

Knowledgeable sources indicate that expected development in rural areas has not yet been achieved, mainly because of improper credit utilization.

More than one reason is suspected for such misuse or misdirection.

These include, among others:

• Diversion of credit money to some unproductive sectors
• Transfer of credit money to other people like money lenders, who exploit the rural people with this money
• Lack of knowledge of proper utilization of the credit.

Here too, reasons for misuse of loans are more than one. We thus consider this problem as a researchable problem.

Research Problem – Example #3

Let’s look at a new headline: Stock Exchange observes the steepest ever fall in stock prices: several injured as retail investors clash with police, vehicles ransacked .

Investors’ demonstration, protest and clash with police pause a problem. Still, it is certainly not a research problem since there is only one known reason for the problem: Stock Exchange experiences the steepest fall in stock prices. But what causes this unprecedented fall in the share market?

Experts felt that no single reason could be attributed to the problem. It is a mix of several factors and is a research problem. The following were assumed to be some of the possible reasons:

• The merchant banking system;
• Liquidity shortage because of the hike in the rate of cash reserve requirement (CRR);
• IMF’s warnings and prescriptions on the commercial banks’ exposure to the stock market;
• Increase in supply of new shares;
• Manipulation of share prices;
• Lack of knowledge of the investors on the company’s fundamentals.

The choice of a research problem is not as easy as it appears. The researchers generally guide it;

• own intellectual orientation,
• level of training,
• experience,
• knowledge on the subject matter, and
• intellectual curiosity.

Theoretical and practical considerations also play a vital role in choosing a research problem. Societal needs also guide in choosing a research problem.

Once we have chosen a research problem, a few more related steps must be followed before a decision is taken to undertake a research study.

These include, among others, the following:

• Statement of the problem.
• Justifying the problem.
• Analyzing the problem.

A detailed exposition of these issues is undertaken in chapter ten while discussing the proposal development.

A clear and well-defined problem statement is considered the foundation for developing the research proposal.

It enables the researcher to systematically point out why the proposed research on the problem should be undertaken and what he hopes to achieve with the study’s findings.

A well-defined statement of the problem will lead the researcher to formulate the research objectives, understand the background of the study, and choose a proper research methodology.

Once the problem situation has been identified and clearly stated, it is important to justify the importance of the problem.

In justifying the problems, we ask such questions as why the problem of the study is important, how large and widespread the problem is, and whether others can be convinced about the importance of the problem and the like.

Answers to the above questions should be reviewed and presented in one or two paragraphs that justify the importance of the problem.

As a first step in analyzing the problem, critical attention should be given to accommodate the viewpoints of the managers, users, and researchers to the problem through threadbare discussions.

The next step is identifying the factors that may have contributed to the perceived problems.

Issues of Research Problem Identification

There are several ways to identify, define, and analyze a problem, obtain insights, and get a clearer idea about these issues. Exploratory research is one of the ways of accomplishing this.

The purpose of the exploratory research process is to progressively narrow the scope of the topic and transform the undefined problems into defined ones, incorporating specific research objectives.

The exploratory study entails a few basic strategies for gaining insights into the problem. It is accomplished through such efforts as:

Pilot Survey

A pilot survey collects proxy data from the ultimate subjects of the study to serve as a guide for the large study. A pilot study generates primary data, usually for qualitative analysis.

This characteristic distinguishes a pilot survey from secondary data analysis, which gathers background information.

Case Studies

Case studies are quite helpful in diagnosing a problem and paving the way to defining the problem. It investigates one or a few situations identical to the researcher’s problem.

Focus Group Interviews

Focus group interviews, an unstructured free-flowing interview with a small group of people, may also be conducted to understand and define a research problem .

Experience Survey

Experience survey is another strategy to deal with the problem of identifying and defining the research problem.

It is an exploratory research endeavor in which individuals knowledgeable and experienced in a particular research problem are intimately consulted to understand the problem.

These persons are sometimes known as key informants, and an interview with them is popularly known as the Key Informant Interview (KII).

Reviewing of Literature

A review of relevant literature is an integral part of the research process. It enables the researcher to formulate his problem in terms of the specific aspects of the general area of his interest that has not been researched so far.

Such a review provides exposure to a larger body of knowledge and equips him with enhanced knowledge to efficiently follow the research process.

Through a proper review of the literature, the researcher may develop the coherence between the results of his study and those of the others.

A review of previous documents on similar or related phenomena is essential even for beginning researchers.

Ignoring the existing literature may lead to wasted effort on the part of the researchers.

Why spend time merely repeating what other investigators have already done?

Suppose the researcher is aware of earlier studies of his topic or related topics . In that case, he will be in a much better position to assess his work’s significance and convince others that it is important.

A confident and expert researcher is more crucial in questioning the others’ methodology, the choice of the data, and the quality of the inferences drawn from the study results.

In sum, we enumerate the following arguments in favor of reviewing the literature:

• It avoids duplication of the work that has been done in the recent past.
• It helps the researcher discover what others have learned and reported on the problem.
• It enables the researcher to become familiar with the methodology followed by others.
• It allows the researcher to understand what concepts and theories are relevant to his area of investigation.
• It helps the researcher to understand if there are any significant controversies, contradictions, and inconsistencies in the findings.
• It allows the researcher to understand if there are any unanswered research questions.
• It might help the researcher to develop an analytical framework.
• It will help the researcher consider including variables in his research that he might not have thought about.

Why is reviewing literature crucial in the research process?

Reviewing literature helps avoid duplicating previous work, discovers what others have learned about the problem, familiarizes the researcher with relevant concepts and theories, and ensures a comprehensive approach to the research question.

What is the significance of reviewing literature in the research process?

Reviewing relevant literature helps formulate the problem, understand the background of the study, choose a proper research methodology, and develop coherence between the study’s results and previous findings.

Setting Research Questions, Objectives, and Hypotheses

After discovering and defining the research problem, researchers should make a formal statement of the problem leading to research objectives .

An objective will precisely say what should be researched, delineate the type of information that should be collected, and provide a framework for the scope of the study. A well-formulated, testable research hypothesis is the best expression of a research objective.

A hypothesis is an unproven statement or proposition that can be refuted or supported by empirical data. Hypothetical statements assert a possible answer to a research question.

Step #4: Choosing the Study Design

The research design is the blueprint or framework for fulfilling objectives and answering research questions .

It is a master plan specifying the methods and procedures for collecting, processing, and analyzing the collected data. There are four basic research designs that a researcher can use to conduct their study;

• experiment,
• secondary data study, and
• observational study.

The type of research design to be chosen from among the above four methods depends primarily on four factors:

• The type of problem
• The objectives of the study,
• The existing state of knowledge about the problem that is being studied, and
• The resources are available for the study.

Deciding on the Sample Design

Sampling is an important and separate step in the research process. The basic idea of sampling is that it involves any procedure that uses a relatively small number of items or portions (called a sample) of a universe (called population) to conclude the whole population.

It contrasts with the process of complete enumeration, in which every member of the population is included.

Such a complete enumeration is referred to as a census.

A population is the total collection of elements we wish to make some inference or generalization.

A sample is a part of the population, carefully selected to represent that population. If certain statistical procedures are followed in selecting the sample, it should have the same characteristics as the population. These procedures are embedded in the sample design.

Sample design refers to the methods followed in selecting a sample from the population and the estimating technique vis-a-vis the formula for computing the sample statistics.

The fundamental question is, then, how to select a sample.

To answer this question, we must have acquaintance with the sampling methods.

These methods are basically of two types;

• probability sampling , and
• non-probability sampling .

Probability sampling ensures every unit has a known nonzero probability of selection within the target population.

If there is no feasible alternative, a non-probability sampling method may be employed.

The basis of such selection is entirely dependent on the researcher’s discretion. This approach is called judgment sampling, convenience sampling, accidental sampling, and purposive sampling.

The most widely used probability sampling methods are simple random sampling , stratified random sampling , cluster sampling , and systematic sampling . They have been classified by their representation basis and unit selection techniques.

Two other variations of the sampling methods that are in great use are multistage sampling and probability proportional to size (PPS) sampling .

Multistage sampling is most commonly used in drawing samples from very large and diverse populations.

The PPS sampling is a variation of multistage sampling in which the probability of selecting a cluster is proportional to its size, and an equal number of elements are sampled within each cluster.

Collecting Data From The Research Sample

Data gathering may range from simple observation to a large-scale survey in any defined population. There are many ways to collect data. The approach selected depends on the objectives of the study, the research design, and the availability of time, money, and personnel.

With the variation in the type of data (qualitative or quantitative) to be collected, the method of data collection also varies .

The most common means for collecting quantitative data is the structured interview .

Studies that obtain data by interviewing respondents are called surveys. Data can also be collected by using self-administered questionnaires . Telephone interviewing is another way in which data may be collected .

Other means of data collection include secondary sources, such as the census, vital registration records, official documents, previous surveys, etc.

Qualitative data are collected mainly through in-depth interviews, focus group discussions , Key Informant Interview ( KII), and observational studies.

Process and Analyze the Collected Research Data

Data processing generally begins with the editing and coding of data . Data are edited to ensure consistency across respondents and to locate omissions if any.

In survey data, editing reduces errors in the recording, improves legibility, and clarifies unclear and inappropriate responses. In addition to editing, the data also need coding.

Because it is impractical to place raw data into a report, alphanumeric codes are used to reduce the responses to a more manageable form for storage and future processing.

This coding process facilitates the processing of the data. The personal computer offers an excellent opportunity for data editing and coding processes.

Data analysis usually involves reducing accumulated data to a manageable size, developing summaries, searching for patterns, and applying statistical techniques for understanding and interpreting the findings in light of the research questions.

Further, based on his analysis, the researcher determines if his findings are consistent with the formulated hypotheses and theories.

The techniques used in analyzing data may range from simple graphical techniques to very complex multivariate analyses depending on the study’s objectives, the research design employed, and the nature of the data collected.

As in the case of data collection methods, an analytical technique appropriate in one situation may not be suitable for another.

Writing Research Report – Developing Research Proposal, Writing Report, Disseminating and Utilizing Results

The entire task of a research study is accumulated in a document called a proposal or research proposal.

A research proposal is a work plan, prospectus, outline, offer, and a statement of intent or commitment from an individual researcher or an organization to produce a product or render a service to a potential client or sponsor .

The proposal will be prepared to keep the sequence presented in the research process. The proposal tells us what, how, where, and to whom it will be done.

It must also show the benefit of doing it. It always includes an explanation of the purpose of the study (the research objectives) or a definition of the problem.

It systematically outlines the particular research methodology and details the procedures utilized at each stage of the research process.

The end goal of a scientific study is to interpret the results and draw conclusions.

To this end, it is necessary to prepare a report and transmit the findings and recommendations to administrators, policymakers, and program managers to make a decision.

There are various research reports: term papers, dissertations, journal articles , papers for presentation at professional conferences and seminars, books, thesis, and so on. The results of a research investigation prepared in any form are of little utility if they are not communicated to others.

The primary purpose of a dissemination strategy is to identify the most effective media channels to reach different audience groups with study findings most relevant to their needs.

The dissemination may be made through a conference, a seminar, a report, or an oral or poster presentation.

The style and organization of the report will differ according to the target audience, the occasion, and the purpose of the research. Reports should be developed from the client’s perspective.

A report is an excellent means that helps to establish the researcher’s credibility. At a bare minimum, a research report should contain sections on:

• An executive summary;
• Background of the problem;
• Literature review;
• Methodology;
• Discussion;
• Conclusions and
• Recommendations.

The study results can also be disseminated through peer-reviewed journals published by academic institutions and reputed publishers both at home and abroad. The report should be properly evaluated .

These journals have their format and editorial policies. The contributors can submit their manuscripts adhering to the policies and format for possible publication of their papers.

There are now ample opportunities for researchers to publish their work online.

The researchers have conducted many interesting studies without affecting actual settings. Ideally, the concluding step of a scientific study is to plan for its utilization in the real world.

Although researchers are often not in a position to implement a plan for utilizing research findings, they can contribute by including in their research reports a few recommendations regarding how the study results could be utilized for policy formulation and program intervention.

Why is the dissemination of research findings important?

Dissemination of research findings is crucial because the results of a research investigation have little utility if not communicated to others. Dissemination ensures that the findings reach relevant stakeholders, policymakers, and program managers to inform decisions.

How should a research report be structured?

A research report should contain sections on an executive summary, background of the problem, literature review, methodology, findings, discussion, conclusions, and recommendations.

Why is it essential to consider the target audience when preparing a research report?

The style and organization of a research report should differ based on the target audience, occasion, and research purpose. Tailoring the report to the audience ensures that the findings are communicated effectively and are relevant to their needs.

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What is Research Methodology? Definition, Types, and Examples

Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of the research. Several aspects must be considered before selecting an appropriate research methodology, such as research limitations and ethical concerns that may affect your research.

The research methodology section in a scientific paper describes the different methodological choices made, such as the data collection and analysis methods, and why these choices were selected. The reasons should explain why the methods chosen are the most appropriate to answer the research question. A good research methodology also helps ensure the reliability and validity of the research findings. There are three types of research methodology—quantitative, qualitative, and mixed-method, which can be chosen based on the research objectives.

What is research methodology ?

A research methodology describes the techniques and procedures used to identify and analyze information regarding a specific research topic. It is a process by which researchers design their study so that they can achieve their objectives using the selected research instruments. It includes all the important aspects of research, including research design, data collection methods, data analysis methods, and the overall framework within which the research is conducted. While these points can help you understand what is research methodology, you also need to know why it is important to pick the right methodology.

Why is research methodology important?

Having a good research methodology in place has the following advantages: 3

• Helps other researchers who may want to replicate your research; the explanations will be of benefit to them.
• You can easily answer any questions about your research if they arise at a later stage.
• A research methodology provides a framework and guidelines for researchers to clearly define research questions, hypotheses, and objectives.
• It helps researchers identify the most appropriate research design, sampling technique, and data collection and analysis methods.
• A sound research methodology helps researchers ensure that their findings are valid and reliable and free from biases and errors.
• It also helps ensure that ethical guidelines are followed while conducting research.
• A good research methodology helps researchers in planning their research efficiently, by ensuring optimum usage of their time and resources.

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Types of research methodology.

There are three types of research methodology based on the type of research and the data required. 1

• Quantitative research methodology focuses on measuring and testing numerical data. This approach is good for reaching a large number of people in a short amount of time. This type of research helps in testing the causal relationships between variables, making predictions, and generalizing results to wider populations.
• Qualitative research methodology examines the opinions, behaviors, and experiences of people. It collects and analyzes words and textual data. This research methodology requires fewer participants but is still more time consuming because the time spent per participant is quite large. This method is used in exploratory research where the research problem being investigated is not clearly defined.
• Mixed-method research methodology uses the characteristics of both quantitative and qualitative research methodologies in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method.

What are the types of sampling designs in research methodology?

Sampling 4 is an important part of a research methodology and involves selecting a representative sample of the population to conduct the study, making statistical inferences about them, and estimating the characteristics of the whole population based on these inferences. There are two types of sampling designs in research methodology—probability and nonprobability.

• Probability sampling

In this type of sampling design, a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are:

• Systematic —sample members are chosen at regular intervals. It requires selecting a starting point for the sample and sample size determination that can be repeated at regular intervals. This type of sampling method has a predefined range; hence, it is the least time consuming.
• Stratified —researchers divide the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized, and then a sample can be drawn from each group separately.
• Cluster —the population is divided into clusters based on demographic parameters like age, sex, location, etc.
• Convenience —selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.
• Purposive —participants are selected at the researcher’s discretion. Researchers consider the purpose of the study and the understanding of the target audience.
• Snowball —already selected participants use their social networks to refer the researcher to other potential participants.
• Quota —while designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.

What are data collection methods?

During research, data are collected using various methods depending on the research methodology being followed and the research methods being undertaken. Both qualitative and quantitative research have different data collection methods, as listed below.

Qualitative research 5

• One-on-one interviews: Helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event
• Document study/literature review/record keeping: Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.
• Focus groups: Constructive discussions that usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic.
• Qualitative observation : Researchers collect data using their five senses (sight, smell, touch, taste, and hearing).

Quantitative research 6

• Sampling: The most common type is probability sampling.
• Interviews: Commonly telephonic or done in-person.
• Observations: Structured observations are most commonly used in quantitative research. In this method, researchers make observations about specific behaviors of individuals in a structured setting.
• Document review: Reviewing existing research or documents to collect evidence for supporting the research.
• Surveys and questionnaires. Surveys can be administered both online and offline depending on the requirement and sample size.

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What are data analysis methods.

The data collected using the various methods for qualitative and quantitative research need to be analyzed to generate meaningful conclusions. These data analysis methods 7 also differ between quantitative and qualitative research.

Quantitative research involves a deductive method for data analysis where hypotheses are developed at the beginning of the research and precise measurement is required. The methods include statistical analysis applications to analyze numerical data and are grouped into two categories—descriptive and inferential.

Descriptive analysis is used to describe the basic features of different types of data to present it in a way that ensures the patterns become meaningful. The different types of descriptive analysis methods are:

• Measures of frequency (count, percent, frequency)
• Measures of central tendency (mean, median, mode)
• Measures of dispersion or variation (range, variance, standard deviation)
• Measure of position (percentile ranks, quartile ranks)

Inferential analysis is used to make predictions about a larger population based on the analysis of the data collected from a smaller population. This analysis is used to study the relationships between different variables. Some commonly used inferential data analysis methods are:

• Correlation: To understand the relationship between two or more variables.
• Cross-tabulation: Analyze the relationship between multiple variables.
• Regression analysis: Study the impact of independent variables on the dependent variable.
• Frequency tables: To understand the frequency of data.
• Analysis of variance: To test the degree to which two or more variables differ in an experiment.

Qualitative research involves an inductive method for data analysis where hypotheses are developed after data collection. The methods include:

• Content analysis: For analyzing documented information from text and images by determining the presence of certain words or concepts in texts.
• Narrative analysis: For analyzing content obtained from sources such as interviews, field observations, and surveys. The stories and opinions shared by people are used to answer research questions.
• Discourse analysis: For analyzing interactions with people considering the social context, that is, the lifestyle and environment, under which the interaction occurs.
• Grounded theory: Involves hypothesis creation by data collection and analysis to explain why a phenomenon occurred.
• Thematic analysis: To identify important themes or patterns in data and use these to address an issue.

How to choose a research methodology?

Here are some important factors to consider when choosing a research methodology: 8

• Research objectives, aims, and questions —these would help structure the research design.
• Review existing literature to identify any gaps in knowledge.
• Check the statistical requirements —if data-driven or statistical results are needed then quantitative research is the best. If the research questions can be answered based on people’s opinions and perceptions, then qualitative research is most suitable.
• Sample size —sample size can often determine the feasibility of a research methodology. For a large sample, less effort- and time-intensive methods are appropriate.
• Constraints —constraints of time, geography, and resources can help define the appropriate methodology.

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How to write a research methodology .

A research methodology should include the following components: 3,9

• Research design —should be selected based on the research question and the data required. Common research designs include experimental, quasi-experimental, correlational, descriptive, and exploratory.
• Research method —this can be quantitative, qualitative, or mixed-method.
• Reason for selecting a specific methodology —explain why this methodology is the most suitable to answer your research problem.
• Research instruments —explain the research instruments you plan to use, mainly referring to the data collection methods such as interviews, surveys, etc. Here as well, a reason should be mentioned for selecting the particular instrument.
• Sampling —this involves selecting a representative subset of the population being studied.
• Data collection —involves gathering data using several data collection methods, such as surveys, interviews, etc.
• Data analysis —describe the data analysis methods you will use once you’ve collected the data.
• Research limitations —mention any limitations you foresee while conducting your research.
• Validity and reliability —validity helps identify the accuracy and truthfulness of the findings; reliability refers to the consistency and stability of the results over time and across different conditions.
• Ethical considerations —research should be conducted ethically. The considerations include obtaining consent from participants, maintaining confidentiality, and addressing conflicts of interest.

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Frequently Asked Questions

Q1. What are the key components of research methodology?

A1. A good research methodology has the following key components:

• Research design
• Data collection procedures
• Data analysis methods
• Ethical considerations

Q2. Why is ethical consideration important in research methodology?

A2. Ethical consideration is important in research methodology to ensure the readers of the reliability and validity of the study. Researchers must clearly mention the ethical norms and standards followed during the conduct of the research and also mention if the research has been cleared by any institutional board. The following 10 points are the important principles related to ethical considerations: 10

• Participants should not be subjected to harm.
• Respect for the dignity of participants should be prioritized.
• Full consent should be obtained from participants before the study.
• Participants’ privacy should be ensured.
• Confidentiality of the research data should be ensured.
• Anonymity of individuals and organizations participating in the research should be maintained.
• The aims and objectives of the research should not be exaggerated.
• Affiliations, sources of funding, and any possible conflicts of interest should be declared.
• Communication in relation to the research should be honest and transparent.
• Misleading information and biased representation of primary data findings should be avoided.

Q3. What is the difference between methodology and method?

A3. Research methodology is different from a research method, although both terms are often confused. Research methods are the tools used to gather data, while the research methodology provides a framework for how research is planned, conducted, and analyzed. The latter guides researchers in making decisions about the most appropriate methods for their research. Research methods refer to the specific techniques, procedures, and tools used by researchers to collect, analyze, and interpret data, for instance surveys, questionnaires, interviews, etc.

Research methodology is, thus, an integral part of a research study. It helps ensure that you stay on track to meet your research objectives and answer your research questions using the most appropriate data collection and analysis tools based on your research design.

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• Research methodologies. Pfeiffer Library website. Accessed August 15, 2023. https://library.tiffin.edu/researchmethodologies/whatareresearchmethodologies
• Types of research methodology. Eduvoice website. Accessed August 16, 2023. https://eduvoice.in/types-research-methodology/
• The basics of research methodology: A key to quality research. Voxco. Accessed August 16, 2023. https://www.voxco.com/blog/what-is-research-methodology/
• Sampling methods: Types with examples. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/types-of-sampling-for-social-research/
• What is qualitative research? Methods, types, approaches, examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-qualitative-research-methods-types-examples/
• What is quantitative research? Definition, methods, types, and examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-quantitative-research-types-and-examples/
• Data analysis in research: Types & methods. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/data-analysis-in-research/#Data_analysis_in_qualitative_research
• Factors to consider while choosing the right research methodology. PhD Monster website. Accessed August 17, 2023. https://www.phdmonster.com/factors-to-consider-while-choosing-the-right-research-methodology/
• What is research methodology? Research and writing guides. Accessed August 14, 2023. https://paperpile.com/g/what-is-research-methodology/
• Ethical considerations. Business research methodology website. Accessed August 17, 2023. https://research-methodology.net/research-methodology/ethical-considerations/

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Basic Research Design

What is research design.

• Definition of Research Design : A procedure for generating answers to questions, crucial in determining the reliability and relevance of research outcomes.
• Importance of Strong Designs : Strong designs lead to answers that are accurate and close to their targets, while weak designs may result in misleading or irrelevant outcomes.
• Criteria for Assessing Design Strength : Evaluating a design’s strength involves understanding the research question and how the design will yield reliable empirical information.

The Four Elements of Research Design (Blair et al., 2023)

• The MIDA Framework : Research designs consist of four interconnected elements – Model (M), Inquiry (I), Data strategy (D), and Answer strategy (A), collectively referred to as MIDA.
• Theoretical Side (M and I): This encompasses the researcher’s beliefs about the world (Model) and the target of inference or the primary question to be answered (Inquiry).
• Empirical Side (D and A): This includes the strategies for collecting (Data strategy) and analyzing or summarizing information (Answer strategy).
• Interplay between Theoretical and Empirical Sides : The theoretical side sets the research challenges, while the empirical side represents the researcher’s responses to these challenges.
• Relation among MIDA Components: The diagram above shows how the four elements of a design are interconnected and how they relate to both real-world and simulated quantities.
• Parallelism in Design Representation: The illustration highlights two key parallelisms in research design – between actual and simulated processes, and between the theoretical (M, I) and empirical (D, A) sides.
• Importance of Simulated Processes: The parallelism between actual and simulated processes is crucial for understanding and evaluating research designs.
• Balancing Theoretical and Empirical Aspects : Effective research design requires a balance between theoretical considerations (models and inquiries) and empirical methodologies (data and answer strategies).

Research Design Principles (Blair et al., 2023)

• Integration of Components: Designs are effective not merely due to their individual components but how these components work together.
• Focus on Entire Design: Assessing a design requires examining how each part, such as the question, estimator, and sampling method, fits into the overall design.
• Importance of Diagnosis: The evaluation of a design’s strength lies in diagnosing the whole design, not just its parts.
• Strong Design Characteristics: Designs with parallel theoretical and empirical aspects tend to be stronger.
• The M:I:D:A Analogy: Effective designs often align data strategies with models and answer strategies with inquiries.
• Flexibility in Models: Good designs should perform well even under varying world scenarios, not just under expected conditions.
• Broadening Model Scope: Designers should consider a wide range of models, assessing the design’s effectiveness across these.
• Robustness of Inquiries and Strategies: Inquiries should yield answers and strategies should be applicable regardless of variations in real-world events.
• Diagnosis Across Models: It’s important to understand for which models a design excels and for which it falters.
• Specificity of Purpose: A design is deemed good when it aligns with a specific purpose or goal.
• Balancing Multiple Criteria: Designs should balance scientific precision, logistical constraints, policy goals, and ethical considerations.
• Diverse Goals and Assessments: Different designs may be optimal for different goals; the purpose dictates the design evaluation.
• Early Planning Benefits: Designing early allows for learning and improving design properties before data collection.
• Avoiding Post-Hoc Regrets: Early design helps avoid regrets related to data collection or question formulation.
• Iterative Improvement: The process of declaration, diagnosis, and redesign improves designs, ideally done before data collection.
• Adaptability to Changes: Designs should be flexible to adapt to unforeseen circumstances or new information.
• Expanding or Contracting Feasibility: The scope of feasible designs may change due to various practical factors.
• Continual Redesign: The principle advocates for ongoing design modification, even post research completion, for robustness and response to criticism.
• Improvement Through Sharing: Sharing designs via a formalized declaration makes it easier for others to understand and critique.
• Enhancing Scientific Communication: Well-documented designs facilitate better communication and justification of research decisions.
• Building a Design Library: The idea is to contribute designs to a shared library, allowing others to learn from and build upon existing work.

The Basics of Social Science Research Designs (Panke, 2018)

Deductive and inductive research.

• Starting Point: Begins with empirical observations or exploratory studies.
• Development of Hypotheses: Hypotheses are formulated after initial empirical analysis.
• Case Study Analysis: Involves conducting explorative case studies and analyzing dynamics at play.
• Generalization of Findings: Insights are then generalized across multiple cases to verify their applicability.
• Application: Suitable for novel phenomena or where existing theories are not easily applicable.
• Example Cases: Exploring new events like Donald Trump’s 2016 nomination or Russia’s annexation of Crimea in 2014.
• Theory-Based: Starts with existing theories to develop scientific answers to research questions.
• Hypothesis Development: Hypotheses are specified and then empirically examined.
• Empirical Examination: Involves a thorough empirical analysis of hypotheses using sound methods.
• Theory Refinement: Results can refine existing theories or contribute to new theoretical insights.
• Application: Preferred when existing theories relate to the research question.
• Example Projects: Usually explanatory projects asking ‘why’ questions to uncover relationships.

Explanatory and Interpretative Research Designs

• Definition: Explanatory research aims to explain the relationships between variables, often addressing ‘why’ questions. It is primarily concerned with identifying cause-and-effect dynamics and is typically quantitative in nature. The goal is to test hypotheses derived from theories and to establish patterns that can predict future occurrences.
• Definition: Interpretative research focuses on understanding the deeper meaning or underlying context of social phenomena. It often addresses ‘how is this possible’ questions, seeking to comprehend how certain outcomes or behaviors are produced within specific contexts. This type of research is usually qualitative and prioritizes individual experiences and perceptions.
• Explanatory Research: Poses ‘why’ questions to explore causal relationships and understand what factors influence certain outcomes.
• Interpretative Research: Asks ‘how is this possible’ questions to delve into the processes and meanings behind social phenomena.
• Explanatory Research: Relies on established theories to form hypotheses about causal relationships between variables. These theories are then tested through empirical research.
• Interpretative Research: Uses theories to provide a framework for understanding the social context and meanings. The focus is on constitutive relationships rather than causal ones.
• Explanatory Research: Often involves studying multiple cases to allow for comparison and generalization. It seeks patterns across different scenarios.
• Interpretative Research: Typically concentrates on single case studies, providing an in-depth understanding of that particular case without necessarily aiming for generalization.
• Explanatory Research: Aims to produce findings that can be generalized to other similar cases or populations. It seeks universal or broad patterns.
• Interpretative Research: Offers detailed insights specific to a single case or context. These findings are not necessarily intended to be generalized but to provide a deep understanding of the particular case.

Qualitative, Quantitative, and Mixed-method Projects

• Definition: Qualitative research is exploratory and aims to understand human behavior, beliefs, feelings, and experiences. It involves collecting non-numerical data, often through interviews, focus groups, or textual analysis. This method is ideal for gaining in-depth insights into specific phenomena.
• Example in Education: A qualitative study might involve conducting in-depth interviews with teachers to explore their experiences and challenges with remote teaching during the pandemic. This research would aim to understand the nuances of their experiences, challenges, and adaptations in a detailed and descriptive manner.
• Definition: Quantitative research seeks to quantify data and generalize results from a sample to the population of interest. It involves measurable, numerical data and often uses statistical methods for analysis. This approach is suitable for testing hypotheses or examining relationships between variables.
• Example in Education: A quantitative study could involve surveying a large number of students to determine the correlation between the amount of time spent on homework and their academic achievement. This would involve collecting numerical data (hours of homework, grades) and applying statistical analysis to examine relationships or differences.
• Definition: Mixed-method research combines both qualitative and quantitative approaches, providing a more comprehensive understanding of the research problem. It allows for the exploration of complex research questions by integrating numerical data analysis with detailed narrative data.
• Example in Education: A mixed-method study might investigate the impact of a new teaching method. The research could start with quantitative methods, like administering standardized tests to measure learning outcomes, followed by qualitative methods, such as conducting focus groups with students and teachers to understand their perceptions and experiences with the new teaching method. This combination provides both statistical results and in-depth understanding.
• Research Questions: What kind of information is needed to answer the questions? Qualitative for “how” and “why”, quantitative for “how many” or “how much”, and mixed methods for a comprehensive understanding of both the breadth and depth of a phenomenon.
• Nature of the Study: Is the study aiming to explore a new area (qualitative), confirm hypotheses (quantitative), or achieve both (mixed-method)?
• Resources Available: Time, funding, and expertise available can influence the choice. Qualitative research can be more time-consuming, while quantitative research may require specific statistical skills.
• Data Sources: Availability and type of data also guide the methodology. Existing numerical data might lean towards quantitative, while studies requiring personal experiences or opinions might be qualitative.

References:

Blair, G., Coppock, A., & Humphreys, M. (2023).  Research Design in the Social Sciences: Declaration, Diagnosis, and Redesign . Princeton University Press.

Panke, D. (2018). Research design & method selection: Making good choices in the social sciences.  Research Design & Method Selection , 1-368.

• Research article
• Open access
• Published: 27 January 2011

A multidisciplinary systematic review of the use of diagrams as a means of collecting data from research subjects: application, benefits and recommendations

• Muriah J Umoquit 1 ,
• Peggy Tso 1 , 2 ,
• Helen ED Burchett 3 &
• Mark J Dobrow 1 , 2  

BMC Medical Research Methodology volume  11 , Article number:  11 ( 2011 ) Cite this article

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In research, diagrams are most commonly used in the analysis of data and visual presentation of results. However there has been a substantial growth in the use of diagrams in earlier stages of the research process to collect data. Despite this growth, guidance on this technique is often isolated within disciplines.

A multidisciplinary systematic review was performed, which included 13 traditional healthcare and non-health-focused indexes, non-indexed searches and contacting experts in the field. English-language articles that used diagrams as a data collection tool and reflected on the process were included in the review, with no restriction on publication date.

The search identified 2690 documents, of which 80 were included in the final analysis. The choice to use diagrams for data collection is often determined by requirements of the research topic, such as the need to understand research subjects' knowledge or cognitive structure, to overcome cultural and linguistic differences, or to understand highly complex subject matter. How diagrams were used for data collection varied by the degrees of instruction for, and freedom in, diagram creation, the number of diagrams created or edited and the use of diagrams in conjunction with other data collection methods. Depending on how data collection is structured, a variety of options for qualitative and quantitative analysis are available to the researcher. The review identified a number of benefits to using diagrams in data collection, including the ease with which the method can be adapted to complement other data collection methods and its ability to focus discussion. However it is clear that the benefits and challenges of diagramming depend on the nature of its application and the type of diagrams used.

Discussion/Conclusion

The results of this multidisciplinary systematic review examine the application of diagrams in data collection and the methods for analyzing the unique datasets elicited. Three recommendations are presented. Firstly, the diagrammatic approach should be chosen based on the type of data needed. Secondly, appropriate instructions will depend on the approach chosen. And thirdly, the final results should present examples of original or recreated diagrams. This review also highlighted the need for a standardized terminology of the method and a supporting theoretical framework.

Peer Review reports

Diagrams are graphic representations used to explain the relationships and connections between the parts it illustrates. There are many subcategories of the broader term 'diagram', which are distinguished by the elements they incorporate or their overall topic. Two dominant subcategories include 'concept maps' and 'mind maps'[ 1 ]. Diagrams are typically brought into the research process in later stages of data analysis or when summarizing and presenting final results. It is commonplace to see a diagram illustrating how concepts or themes relate to each other or to explain how the research data relates to an underlying theory. These diagrams can be developed through the researchers' inductive reasoning of the data collected or may be assisted by computer software[ 2 ].

The use of diagrams in earlier stages of the research process (i.e. to collect data) is a relatively new method and is not a common data collection approach at present. However, their use is developing in multiple disciplines, including healthcare research. Diagrams have been used to collect data from research subjects by asking them to either draw a diagram themselves or modify a prototypic diagram supplied by the researcher. The use of diagrams in data collection has been viewed favorably in helping to gather rich data on healthcare topics. These research topics are widely varied and include collecting information to improve patient safety with medication[ 3 ], understanding neighborhood characteristics related to mental well-being[ 4 ], mapping out healthcare networks[ 5 ], evaluating patient educational programs[ 6 , 7 ], understanding how different populations view microbial illnesses[ 8 ], diagramming as part of nursing education that is evidence-based[ 9 ] and involves critical thinking[ 10 , 11 ], to engage youth in healthcare consultations[ 12 ], and to gain insights on physician professional growth[ 13 ] and their accountability relationships[ 14 ].

Despite the increasing use of diagrams in data collection, there lacks a strong "supportive structure" (pg. 343) for researchers choosing this method[ 15 ]. The use of diagrams in data collection has developed independently in multiple disciplines under a number of different names, making knowledge transfer regarding this technique difficult. For example, little has been published on process mapping outside of the organizational literature until fairly recently[ 5 , 16 , 17 ]. This has limited the exchange of best practices between disciplines. Researchers are often starting from scratch when designing their diagramming data collection approaches and their analysis of the unique data collected[ 15 ].

By conducting a multidisciplinary systematic review, as defined in the PRISMA statement[ 18 ], we hope to consolidate lessons learned and offer recommendations for researchers in healthcare and other disciplines about how diagrams may be incorporated into their data collection process. The questions that guided our search for relevant studies were:

(1) What drives the selection of a diagramming approach for data collection?

(2) What are the different approaches to diagramming for data collection?

(3) What are the different approaches to analyzing data collected with diagramming?

(4) What are the benefits and challenges of using diagramming for data collection?

Diagramming techniques used for data collection in the research process is a challenging area to review, given the variable terminology across, and even within, fields. A preliminary survey of the literature helped identify some key terminology used in different disciplines (e.g. "graphic elicitation" or "participatory diagramming"). The terms used in the titles and abstracts of the preliminary articles identified, as well as the keywords used to index them in databases, formed the basis of our multidisciplinary search strategy. We combined these specific terms with general 'diagram' terms and with general 'data collection' and/or 'analysis' terms.

In December 2009, we electronically searched 13 indexed sources, including traditional health care related indexes and non-health focused indexes (EMBASE; HealthSTAR; Medline; Cumulative Index to Nursing and Allied Health Literature; GEOBASE; InfoTrac Environmental Issues & Policy eCollection; ProQUEST Dissertations; Design and Applied Arts Index; Education Resources Information Center; International Bibliography of the Social Sciences; PsychINFO; Public Affairs Information Services; and Social Science Citation Index). To ensure that all appropriate references were identified and to limit publication bias, non-indexed sources were also searched via general search tools (i.e. Google Scholar and Google Books) to uncover any additional publications. To supplement the search, 35 experts, identified by our searches, were contacted and asked to identify additional relevant articles and grey literature.

Reference Manager 11 was used to support the review. Following the removal of duplicates, articles were screened based on their title and abstract. The full-text was then screened for articles not excluded based on their title/abstract. Articles were excluded if they were not written in English, did not use diagramming techniques in the data collection process (i.e. research subjects did not create or edit diagrams) or were not evaluative or reflective about the data collection process and/or analysis of data collected from diagramming methods. No publication date or publication type restrictions were imposed; research studies, theoretical articles, method articles and opinion pieces were included if they met the above criteria.

The screening was undertaken by two authors (MJU, PT). Double screening was done at regular intervals to ensure inter-rater reliability. Further, the two researchers met weekly during the screening and data extraction phases to discuss the nuances of the articles and to resolve differences by deliberation until consensus was reached.

A total of 2690 references were identified, after the removal of duplicates. Given our search had no publication date restrictions and included dissertations, full-text articles were sometimes difficult to retrieve. Authors were contacted when the article could not be found online or through the University of Toronto's library system. While 4 articles were retrieved in this manner, 27 full-text articles still could not be found and were ultimately excluded. In total, 233 full-text articles were screened and a total of 80 articles were included in the study's review. Figure 1 presents a flow diagram of our search and screening. Data was extracted on the general characteristics of the articles and the four objectives detailed earlier (see Table 1 ).

Flow of articles through the systematic review .

General characteristics

Of the 80 articles included in our review, 53 were published studies[ 1 , 4 – 15 , 19 – 58 ], 19 were dissertations[ 59 – 77 ], 2 were books[ 78 , 79 ] and 6 represented grey literature[ 3 , 80 – 84 ], including unpublished working papers submitted by key experts and reports available on the internet. These articles were published between 1986 and 2010, with the majority published after 2000 and a substantial increase after 2006. This suggests that interest in these techniques has been increasing in recent years.

The most common discipline, determined by the lead author's affiliation and/or publication title, was from the education field. Other disciplines included healthcare, engineering, environmental science, geography, industrial design, psychology, and social science. The majority of articles clearly specified the study sample size, which averaged 36 research subjects, with a range of 2 to 243. Diagramming methods were used with a wide variety of research subjects, including students (elementary to graduate school), farmers, nurses, physicians, engineers, administrators and graphic designers.

What drives the selection of a diagramming approach for data collection?

The majority of articles specified at least one explicit reason why a form of diagramming was selected for data collection. These reasons fall into two broad categories: requirements or challenges of the research topic and the unique dataset that results from using diagrams.

The specific research topic examined was the most common reason for researchers choosing a diagramming technique for data collection. For some research topics, past studies have validated diagramming data collection techniques as a useful way to collect data. For example, research has established the usefulness of diagrams in collecting data about research subjects' knowledge or cognitive structures[ 19 – 22 , 59 , 80 ]. Diagrams in data collection have also been validated as a means of measuring changes over time[ 6 , 10 , 20 , 22 – 24 , 60 , 85 ] and differences between participant groups[ 20 , 25 , 61 , 81 ]. Diagramming methods were also sought out when research topics were not conducive to the more common qualitative data collection methods, such as interviews alone. These reasons include a research topic that deals with a population with linguistic, cultural, social or intuitional barriers the researcher wants to overcome[ 12 , 14 , 15 , 26 – 29 , 79 ] or with highly complex subject matter[ 12 , 14 , 25 , 30 – 32 , 85 ]. Examples of highly complex subject matters include the abstract nature of the research topic of 'pedagogical constructs'[ 25 ] and the multifaceted and diverse nature of 'clinical accountability relationships'[ 14 ].

Secondly, researchers sought out diagramming data collection methods because of the benefits previous studies found regarding the quality and uniqueness of the collected dataset. When research subjects drew diagrams without prompts, previous studies concluded that it minimized the influence of the researcher on the participant and their responses[ 1 , 33 – 35 , 61 , 62 , 81 , 82 ]. Studies have also found that diagramming is a reflective tool for the research subjects[ 28 , 29 , 36 , 63 ]. Since diagrams can represent both concrete and theoretical notions[ 37 ], diagramming offers a more holistic coverage of the topic[ 29 , 38 , 61 ], with more uncensored and unique data gathered[ 1 , 24 , 28 , 35 , 39 , 40 , 58 ] than more traditional qualitative data collection methods.

What are the different approaches to diagramming for data collection?

A range of applications were identified, which varied widely based on the degree of instruction, degree of freedom in diagram creation, the number of diagrams created or edited and the use of diagram in conjunction with other data collection methods.

Half of the studies did not report the details of the instructions provided to the research subjects, except for describing the basic request to create a diagram. One study explicitly observed that specific instructions are needed to ensure the research participants create a diagram and not another form of written material[ 32 ], such as a drawing or table. Simple or short instructions were often given to research subjects when the diagram sought by the researchers did not have to conform to a rigid structure, such as life-cycle[ 13 ] and professional practice diagrams[ 32 ].

When the researcher sought highly structured diagrams, the degree of instruction provided to the research subjects ranged from the preferred method of giving specific and detailed instructions on what elements should be included (e.g. hierarchies, arrows) to showing an example of the type of diagram the researcher would like the participant to create. For example, in comparison to other diagramming techniques, concept maps have a fairly rigid definition and a very specific set of elements that the end diagram should contain. Such diagrams may require more detailed instructions. One study had associate nursing degree students draw their own concept maps after a 20-minute introductory tutorial, presentation of a sample diagram, discussion and question period, and instructions listing all elements to be included (e.g. arrangement of items, hierarchal order, linking concepts with arrow, labeling propositions, identifying cross-links/relationships)[ 9 ]. In some instances, research subjects were given the opportunity to practice the diagramming method and receive corrective feedback prior to data collection[ 19 , 23 , 41 , 64 ].

It was most common for research subjects to create an original diagram on their own, in groups or a combination of both. Alternatively, some studies had the participant edit either a designated diagram provided by the researcher[ 3 , 14 , 15 , 42 ] or a researcher-created diagram generated by the researcher during the interview with participant input[ 4 , 5 , 7 , 43 ]. A few studies also chose the middle ground between original and prepared diagrams. For example, some provided a central concept or word to create the diagram around[ 14 , 44 ], or included some words or shapes to fill in on a prepared diagram[ 45 ] and others gave research subjects a list of words to use in the creation of their diagram[ 65 , 80 ].

Half of the studies used diagrams at multiple times within the data collection process as a means of comparison. A subset used a pre-/post- (or time series) approach to data collection, allowing researchers to track changes before, after, and sometimes during an intervention. This was found primarily within the discipline of education. For example, Rios asked a sample of teachers to create concept maps at multiple time intervals in order to identify their conceptual models and examine the impact of student interactions on the teachers' subject matter structure or vice versa[ 66 ].

Some researchers explicitly expressed the idea that diagrams alone would not capture complete perspectives from the research subjects[ 57 , 77 ], suggesting that diagrams should be used in combination with other data collection methods. The majority of the studies did use diagramming data collection techniques in addition to other methods. In some cases the additional data collection methods were used explicitly in conjunction with the diagramming techniques, such as creating the diagram within interviews or discussion of the diagrams in later focus groups or interviews[ 8 , 23 , 39 , 59 , 60 , 67 ].

What are the different approaches to analyzing data collected with diagramming?

The majority of the articles reported details about the analysis of diagram data. The use of only quantitative or qualitative analysis, or a mixture of both types of analysis was fairly equally distributed among the articles. Within each of these three categories of analysis, there were a variety of different techniques used that are briefly outlined below.

The majority of studies comparing diagrams across time or across research subjects chose either quantitative techniques only or a mix of qualitative and quantitative techniques for their analysis. Quantitative analysis techniques included counting (e.g. number of concepts identified, number of links between concepts, number of examples given, levels in hierarchy) and scoring. The two most common scoring methods were structural scoring and relational scoring[ 22 ]. Structural scoring refers to when weights are assigned to hierarchical structures, links between concepts and other elements. For example, a link between two concepts may be 10 points, an example 1 point and invalid examples and cross links 0 points[ 40 ]. Relational scoring reflects the quality or importance of each concept or link as determined by the researcher, by comparison to a similar diagram created by an expert or by other research subjects[ 36 , 38 , 60 , 62 , 68 ]. Some studies using quantitative analysis showed diagrams to illustrate how the final counting and scoring of a diagram was completed in the presentation of final study results[ 35 , 40 , 41 , 46 – 49 , 54 , 62 ]. For example, Kesby had focus groups in Zimbabwe create scored diagrams with local materials of rocks, string and bottle caps[ 54 ]. These diagrams were photographed and also reproduced on computer for legibility. Including an original diagram in the presentation of results also helps to orient the reader to the type of diagram that was used.

Studies which had diagrams completed or edited in the presence of the researcher, included additional data collection methods, and/or studies using less structured diagrams to collect data were likely to use either qualitative techniques only or a mix of qualitative and quantitative techniques for their analysis. For example, Haidet et al. gave medical school research subjects less structure and encouraged creativity in their diagramming exercise within interviews[ 13 ]. The diagram was used as a prompt to stimulate discussion, which was then analyzed through the interview transcripts. The diagram itself was then displayed in the final results to visually summarize the verbal exchange. Qualitative analysis included thematic and content analysis of the diagrams and additional data sources, such as transcripts, to identify prominent topics, themes and patterns in the diagrams[ 13 , 25 , 26 , 34 , 63 , 66 , 69 – 71 ].

In some studies that used mixed-methods, the collected diagrams were the primary source of data and guided the analysis of additional data sources, for example, by providing the core themes for transcript analysis. In other cases the additional data sources played the dominant role in analysis and the diagrams were used almost as verification or visual representation to illustrate conclusions[ 72 ].

What are the benefits and challenges of using diagramming for data collection?

Some of the benefits to using diagrams for data collection have already been discussed in the section on why researchers chose diagramming data collection approaches. In addition to these, diagramming approaches that were seen as complementary to other data collection approaches were commonly used in interviews and focus groups[ 60 , 73 ]. They were found to help focus discussions on particular themes[ 32 ] and enabled research subjects to more easily reflect on a topic or their beliefs by helping them to express thoughts in a more structured and organized manner[ 50 , 51 ]. The use of diagrams was also seen to increase recall[ 52 ] and self-reflectiveness[ 53 , 54 ]. In 1992, Powell found that interviews which made use of diagramming approaches were more introspective and tended to be more theoretical and philosophical than those that did not use diagramming methods[ 25 ].

Over half of the articles discussed at least one challenge of using a diagramming method for data collection. Interestingly, these challenges were often contradicted by other articles. All studies completed their data collection with diagrams, with some reporting that the diagramming allowed research subjects to overcome challenges of verbal communication[ 12 , 14 , 15 , 26 – 29 , 75 , 79 ]. However, many studies found that at least some of the research subjects expressed difficulty or discomfort with the diagramming task[ 1 , 9 , 10 , 14 , 28 , 35 , 55 , 56 , 58 , 62 , 74 , 76 , 83 ]. Some identified the ease and speed of data collection as benefits of using diagramming approaches[ 24 , 31 , 54 ], while others saw it as being time-intensive, particularly for analysis[ 6 , 11 , 26 , 62 ]. Related to the visual organization and structure of knowledge that the diagrams presented, an advantage to using diagramming approaches for data collection is their ability to obtain unique and unsolicited data[ 7 , 14 , 15 , 26 , 29 , 33 , 42 , 43 , 58 ]. In contrast, there were also concerns regarding the data it did not collect, such as non-verbal communication, that require the discretion and experience of researchers to identify and interpret[ 15 , 24 , 84 ]. These contradictions illustrate that the benefits and challenges to using diagramming approaches for data collection depend on the application and type of diagram used in each research study.

This systematic review represents the first overview of diagrams being used as a data collection approach in multiple disciplines. In 2006, Nesbit & Adesope[ 86 ] conducted a widely cited meta-analysis looking at peer-reviewed articles focusing on learning with concept and knowledge maps and found that the interest in using diagrams appeared to be on the rise[ 86 ]. While our systematic review concurs that interest is growing, it differs from their meta-analysis in two ways. Firstly our definition of a diagram is much broader, encompassing a variety of diagrams that extend beyond concept and knowledge maps. As well as the structured diagrams that Nesbit & Adescope focused on, our review also includes less structured diagrams, such as the life-cycle and professional practice discussed in our results section. Secondly, our focus is solely on diagrams being used as a data collection approach, whereas their meta-analysis included diagrams used as analysis techniques as well.

Given our broad definition of a diagram, we have reviewed approaches for collecting data through a wide spectrum of diagrams, from highly structured concept maps to less defined diagrams. We have provided an overview of the instruction options for research subjects, the creation and analysis of diagramming as a data collection approach, as well as highlighted some of the benefits and challenges. While there is variation regarding the guidance in instructions and approaches to the construction of different diagrams, use of diagrams as a data collection tool as a whole is clearly increasing in healthcare and in other disciplines. This systematic review is the first step in consolidating this information to assist in the refinement of this approach. For those considering using diagramming as a data collection approach, we offer three recommendations. Firstly, the diagrammatic approach should be chosen based on the type of data needed to answer the research question(s). Secondly, based on the diagrammatic approach chosen, it is important to select the appropriate instructions needed. Finally, presentation of final results should include examples of the original or recreated diagrams.

Choice of Diagramming Approach

The most important considerations for choosing the diagramming approach is the type of data needed to answer the research question (e.g., examining change over time, exploring people's experiences or views) and the type of analysis preferred by the researcher. For example, highly structured diagrams allowed for valid quantitative analysis, such as counting and ranking, which could be compared across research subjects. It should be noted that there is some controversy whether items should even be counted and that both an over- or under-reliance may be dangerous to the final research conclusions[ 28 ]. In comparison, other approaches that used a less structured diagrams relied heavily on qualitative analysis.

Instruction and Creation

The appropriateness of different approaches to instructions to guide diagram creation is an important consideration in ensuring the validity of data. It is clear from our review that the initial instructions given to research subjects varied in structure but had a great impact on the resulting diagrams and their potential for different analysis techniques. If researchers require highly structured diagrams it may be useful to give research subjects more detailed instructions and the opportunity for practice and feedback[ 30 , 64 ].

Presentation of results

The last recommendation is that studies using diagramming data collection approaches should include visual presentations of the findings in their results sections. The use of diagrams often results in the collection of unique and unsolicited data through a visual component, which can then be displayed along with the final analysis. Just as diagrams can provide data not easily obtained through verbal data collection techniques, visual presentation of the collected diagrams may provide insights not as easily grasped through verbal communication of study results. While providing a scanned image of the original diagram can be difficult at times, it is also possible to present a photograph of the original diagram or a computer-generated recreation of the diagram. This is especially important given the variation in terminology between disciplines, as it relays to the reader the type and structure of diagrams created or used.

In addition to the recommendations for researchers considering the use of diagramming data collection approaches, this multidisciplinary review also identifies areas where future research is needed. This review required a substantial amount of preliminary work to understand the terminology used to describe diagrams and this data collection approach across different disciplines and fields. The intent was to devise a sensitive search, so as to cast a wide net in order to capture articles in a range of disciplines where the terminology is not standardized. Cole et al. illustrate this issue by identifying over a dozen different terms that are used to describe concept maps[ 56 ]. Thus far, development of terminology has focused on the end result, i.e. what type of diagram is created based on the elements it contains, rather than focusing on the actual data collection approach itself. This has created different data collection approaches that use diagrams separately, isolating research done across disciplines and even within disciplines. Therefore, it is our recommendation that efforts are directed towards standardizing the terminology for this data collection method. This would allow researchers to maintain the work they have done regarding specific types of diagrams, whilst providing an umbrella term to help with the sharing of best practices. Future research should also be directed at identification of the underpinning theory of the method as the review demonstrated a gap in this area[ 15 , 32 , 35 ]. Such a theory may help to further inform researchers regarding the appropriate use and applications for diagramming data collection approaches.

A limitation of our review is that the database search strategy did not capture general articles on visual data collection methods, which may include specific information on diagramming data collection approaches. However the non-indexed searches and articles identified by experts did pick up some of these articles. While efforts were made to contact authors to retrieve articles from our search, twenty-seven full-text articles were irretrievable. Ten of these were dissertations and five were books. This may have contributed to an incomplete representation of what the literature has to offer about diagramming data collection approaches.

There has been a growing interest in the use of diagrams for data collection in the research process over recent years, as shown by the increase in publications and the wide range of approaches developed for diagramming data collection and diagram data analysis. As noted earlier, diagrams have been used to collect rich data on a variety of healthcare topics and it is expected that the use of this method will continue to grow. The results of this multidisciplinary systematic review provide an overview of the application of diagrams in research data collection and the methods for analyzing the unique datasets elicited. Recommendations are presented to assist researchers considering the use of diagrams in their data collection process. This review also highlighted the need for a standardized terminology of the method and a supporting theoretical framework.

Wheeldon J, Faubert J: Framing experience: concept maps, mind maps, and data collection in qualitative research. International Journal of Qualitative Methods. 2009, 8: 68-83.

Google Scholar  

Forbes MA: Hope in the older adult with chronic illness: A comparison of two research methods in theory building. Advances in Nursing Science. 1999, 22: 74-87.

Article   CAS   PubMed   Google Scholar  

Jafri T, Lyons MN, Clarkson PJ: The supply of medicines in the NHS. 2008, Improving Patient Safety: Cambridge, UK

O'Campo P, Salmon C, Burke J: Neighbourhoods and mental well-being: what are the pathways?. Health and Place. 2009, 15: 56-68.

Article   PubMed   Google Scholar  

Pluto DM, Hirshorn BA: Process mapping as a tool for home health network analysis. Home Health Care Services Quarterly. 2003, 22: 1-16. 10.1300/J027v22n02_01.

Franca S, d'Ivernois JF, Marchand C, Haenni C, Ybarra J, Golay A: Evaluation of nutritional education using concept mapping. Patient Education and Counseling. 2004, 52: 183-192. 10.1016/S0738-3991(03)00037-5.

Marchand C, d'Ivernois JF, Assal JP, Slama G, Hivon R: An analysis, using concept mapping, of diabetic patients' knowledge, before and after patient education. Medical Teacher. 2002, 24: 90-99. 10.1080/01421590120091087.

Jones MG, Rua MJ: Conceptual representations of flu and microbial illness held by students, teachers, and medical professionals. Social Science and Mathematics. 2008, 108: 263-278.

Article   Google Scholar  

Abel WM, Freeze M: Evaluation of concept mapping in an associate degree nursing program. Journal of Nursing Education. 2006, 45: 356-364.

PubMed   Google Scholar  

Daley BJ, Shaw CR, Balistrieri T, Glasenapp K, Piacentine L: Concept maps: a strategy to teach and evaluate critical thinking. Journal of Nursing Education. 1999, 38: 42-47.

CAS   PubMed   Google Scholar  

Hicks-Moore SL, Pastirik PJ: Evaluating critical thinking in clinical concept maps: A pilot study. International Journal of Nursing Education Scholarship. 2006, 3: 1-15. 10.2202/1548-923X.1314.

Coad J: Using art-based techniques in engaging children and young people in health care consultations and/or research... including commentary by Bishop V and Picard C. Journal of Research in Nursing. 2007, 12: 487-497. 10.1177/1744987107081250.

Haidet P, Hatem DS, Fecile ML, Stein HF, Haley H-L, Kimmel B, et al: The role of relationships in the professional formation of physicians: Case report and illustration of an elicitation technique. Patient Education and Counseling. 2008, 72: 382-387. 10.1016/j.pec.2008.05.016.

Umoquit MJ, Dobrow MJ, Lemieux-Charles L, Ritvo PG, Urbach DR, Wodchis WP: The efficiency and effectiveness of utilizing diagrams in interviews: An assessment of participatory diagramming and graphic elicitation. BMC Medical Research Methodology. 2008, 8-

Crilly N, Blackwell A, Clarkson P: Graphic elicitation: using research diagrams as interview stimuli. Qualitative Research. 2006, 6: 341-366. 10.1177/1468794106065007.

Jun GT, Ward JR, Morris ZS, Clarkson PJ: Health care process modelling: which method when?. International Journal for Quality in Health Care. 2009, 21: 214-224. 10.1093/intqhc/mzp016.

Jun GT, Ward JR, Clarkson PJ: Systems modelling approaches to the design of safe healthcare delivery:ease of use and usefulness percived by healthcare works. Ergonomics. 2010, 53: 829-847. 10.1080/00140139.2010.489653.

Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gotzsche PC, Ioannidis JP, et al: The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Medicine. 2009, 6: e100100-10.1371/journal.pmed.1000100.

Zhang L, Wang Y, Dong B, Zhou Z: The comparison study of Chinese and American secondary school students' knowledge structure--An experimental research based on concept map assessment technique. Frontiers of Education in China. 2009, 4: 286-297. 10.1007/s11516-009-0015-0.

Hay DB: Using concept maps to measure deep, surface and non-learning outcomes. Studies in Higher Education. 2007, 32: 39-57. 10.1080/03075070601099432.

Lavigne NC, Salkind SJ, Yan J: Exploring college students' mental representations of inferential statistics. The Journal of Mathematical Behavior. 2008, 27: 11-32. 10.1016/j.jmathb.2007.10.003.

West DC, Park JK, Pomeroy JR, Sandoval J: Concept mapping assessment in medical education: A comparison of two scoring systems. Medical Education. 2002, 36: 820-826. 10.1046/j.1365-2923.2002.01292.x.

Carter G, Jones MG, Rua M: Effects of partner's ability on the achievement and conceptual organization of high-achieving fifth-grade students. Science Education. 2002, 87: 94-111. 10.1002/sce.10031.

Hay DB, Wells H, Kinchin IM: Quantitative and qualitative measures of student learning at university level. Higher Education. 2008, 56: 221-240. 10.1007/s10734-007-9099-8.

Powell RR: The influence of prior experiences on pedagogical constructs of traditional and nontraditional preservice teachers. Teaching and Teacher Education. 1992, 8: 225-238. 10.1016/0742-051X(92)90022-U.

Kesby M: Participatory diagramming as a means to improve communication about sex in rural Zimbabwe: a pilot study. Social Science & Medicine. 2000, 50: 1723-1741.

Article   CAS   Google Scholar  

Van der Riet M: Diagramming as mediational means: Vygotskian theory and participatory research. South African Journal of Psychology. 2008, 38: 455-465.

Wheeldon J: Is a picture worth a thousand words? Using mind maps to facilitate participant recall in qualitative research. Qualitative Report.

Bagnoli A: Beyond the standard interview: The use of graphic elicitation and arts-based methods. Qualitative Research. 2009, 9: 547-571. 10.1177/1468794109343625.

Lim SE, Chan Cheng PW, Lam MS, Ngan SF: Developing reflective and thinking skills by means of semantic mapping strategies in kindergarten teacher education. Early Child Development and Care. 2003, 173 (1): 55-72. 10.1080/0300443022000022422.

Ozesmi U, Ozesmi SL: Ecological models based on people's knowledge: A multi-step fuzzy cognitive mapping approach. Ecological Modeling. 2004, 176: 43-64. 10.1016/j.ecolmodel.2003.10.027.

Varga-Atkins T, O'Brien M: From drawings to diagrams: Maintaining researcher control during graphic elicitation in qualitative interviews. International Journal of Research & Methods in Education. 2009, 32: 53-67.

Williams CG: Using concept maps to assess conceptual knowledge of function. Journal for Research in Mathematics Education. 1998, 29: 414-421. 10.2307/749858.

Strean WB, Holt NL: Coaches', athletes', and parents' perceptions of fun in youth sports: assumptions about learning and implications for practice. AVANTE. 2000, 6: 83-98.

Wheeldon J: Mapping mixed methods research: Methods, measures, and meaning. Journal of Mixed Methods Research. 2010, 48: 87-102. 10.1177/1558689809358755.

Rye JA, Rubba PA: An exploration of the concept map as an interview tool to facilitate the externalization of students' understandings about global atmospheric change. Journal of Research in Science Teaching. 1998, 35: 521-546. 10.1002/(SICI)1098-2736(199805)35:5<521::AID-TEA4>3.0.CO;2-R.

Lourdel N, Gondran N, Laforest V, Debray B, Brodhag C: Sustainable development cognitive map: A new method of evaluating student understanding. International Journal of Sustainability in Higher Education. 2007, 8: 170-182. 10.1108/14676370710726634.

Koul R, Clariana RB, Salehi R: Comparing several human and computer-based methods for scoring concept maps and essays. Journal of Educational Computing Research. 2005, 32: 227-239. 10.2190/5X9Y-0ETN-213U-8FV7.

Shymansky JA, Yore LD, Treagust DF, Thiele RB, Harrison A, Waldrip BG, et al: Examining the construction process: A study of changes in level 10 students' understanding of classical mechanics. Journal of Research in Science Teaching. 1997, 34: 571-593. 10.1002/(SICI)1098-2736(199708)34:6<571::AID-TEA3>3.0.CO;2-K.

West DC, Pomeroy JR, Park JK, Gerstenberger EA, Sandoval J: Critical thinking in graduate medical education: A role for concept mapping assessment?. Journal of the American Medical Association. 2000, 284: 1105-1110. 10.1001/jama.284.9.1105.

Lian MWS: An investigation into high-achiever and low-achiever knowledge organisation and knowledge processing in concept mapping: A case study. Research in Science Education. 1998, 28: 337-352. 10.1007/BF02461567.

Crilly N, Clarkson P, Blackwell A: Using research diagrams for member validation in qualitative research. Diagrams. 2006, 4045: 258-262.

Cox P, Niewoehner J, Pidgeon N, Gerrard S, Fischhoff B, Riley D: The use of mental models in chemical risk protection: Developing a generic workplace methodology. Risk Analysis. 2003, 23: 311-324. 10.1111/1539-6924.00311.

Koury K, Hollingsead C, Fitzgerald G, Miller K, Mitchem K, Tsai HH, et al: Case-based instruction in different delivery contexts: The impact of time in cases. Journal of Interactive Learning Research. 2009, 20: 445-467.

Gill PE, Persson M: On using concept-maps to study school-children's understanding of leisure-time. Leisure Studies. 2008, 27: 213-220. 10.1080/02614360802048795.

Wheeldon J: To guide or provoke? Maps, pedagogy, and the value(s) of teaching criminal justice ethics. Criminal Justice Education.

Mouratiadou I, Moran D: Mapping public participation in the Water Framework Directive: A case study of the Pinios River Basin, Greece. Ecological Economics. 2007, 62: 66-76. 10.1016/j.ecolecon.2007.01.009.

Kimber K, Pillay H, Richards C: Technoliteracy and learning: An analysis of the quality of knowledge in electronic representations of understanding. Computers & Education. 2007, 48: 59-79.

Artiles AJ, Barreto RM, Pena L, McClafferty K: Pathways to teacher learning in multicultural contexts - A longitudinal case study of two novice bilingual teachers in urban schools. Remedial and Special Education. 1998, 19: 70-90. 10.1177/074193259801900203.

Farrell TSC: Critical reflection in a TESL Course: Mapping conceptual change. ELT Journal. 2008, 63: 221-229. 10.1093/elt/ccn058.

Lourdel N, Gondran N, Laforest V, Brodhag C: Introduction of sustainable development in engineers' curricula: Problematic and evaluation methods. International Journal of Sustainability in Higher Education. 2005, 6: 254-264. 10.1108/14676370510607223.

Naykki P, Jarvela S: How pictorial knowledge representations mediate collaborative knowledge construction in groups. Journal of Research on Technology in Education. 2008, 40: 359-

Conceicao SC, Taylor LD: Using a constructivist approach with online concept maps: relationship between theory and nursing education. Nursing Education Perspectives. 2007, 28: 268-275.

Kesby M: Participatory diagramming: Deploying qualitative methods through an action research epistemology. Area. 2000, 32: 423-435. 10.1111/j.1475-4762.2000.tb00158.x.

Ahmed R, Ali NA: Performance appraisal decision in Malaysian public service. International Journal of Public Sector Management. 17: 48-64. 10.1108/09513550410515565. 4 A.D

Cole C, Lin Y, Leide J, Large A, Beheshti J: A classification of mental models of undergraduates seeking information for a course essay in history and psychology: preliminary investigations into aligning their mental models with online thesauri. Journal of the American Society for Information Science & Technology. 2007, 58: 2092-2104.

Rowe AL, Cooke NJ: Measuring mental models: Choosing the right tools for the job. Human Resources Development Quarterly. 1995, 6: 243-255. 10.1002/hrdq.3920060303.

Wheeldon J: Learning from Latvia: Adoption, adaptation, and evidence based justice reform. Journal of Baltic Studies.

Garegae KGM: . Teachers, beliefs about mathematics, its teaching and learning and the communication of these beliefs to students: A case study in Botswana. Ph.D. 2002, Canada: The University of Manitoba

McWhirter LJ: Conceptual development and retention within the learning cycle. Ph.D. 1998, United States -- Oklahoma: The University of Oklahoma

Williams CG: . Using concepts maps to determine differences in the concept image of function held by students in reform and traditional calculus classes. Ph.D. 1994, United States -- California: University of California

Puukari S: . Video programmes as learning tools: Teaching the gas laws and behaviour of gases in Finnish and Canadian senior high schools. Ed.D. 2003, Finland: Jyvaskylan Yliopisto

Mathews S: An ethnographic examination of perspective consciousness and intercultural competence among social studies student-teachers in Kenya, East Africa. Ph.D. 2008, United States -- Indiana: Indiana University

Skidmore L: Concept mapping to promote meaningful learning at the community college level. 2008, United States -- Minnesota: Walden University, Ed.D

Yin Y, Vanides J, Ruiz-Primo MA, Ayala CC, Shavelson R: A Comparison of Two Construct-a-Concept-Map Science Assessments: Created Linking Phrases and Selected Linking Phrases. 2004, The Regents of the University of California, 1-28. unknown CSE Report 624

Rios JM: Studies of contrast: Relationships between subject matter structures and teaching. 1995, United States -- Wisconsin: The University of Wisconsin, Ph.D

Feldsine JE: The construction of concept maps facilitates the learning of general college chemistry: A case study. 1987, United States -- New York: Cornell University, Ph.D

Butler KA: Scaffolding software: How does it influence student conceptual understanding and motivation?. 2004, United States -- Illinois: Southern Illinois University at Carbondale, Ph.D

Alexander LM: Variations of professional identity over time: A study of physician assistants. 2003, United States -- District of Columbia: The George Washington University, Ed.D

Cantu DA: A naturalistic investigation of the relationship between secondary social studies teachers' beliefs and practice. 1997, United States -- Illinois: Southern Illinois University at Carbondale, Ph.D

Cozza B: Concept mapping through logs and metacognitive reflection during third graders' scientific problem-solving. 1996, United States -- New York: Fordham University, Ph.D

Ballard BG: Preservice teachers' beliefs about classroom management before and after student teaching. 2002, United States -- Nevada: University of Nevada, Las Vegas, Ed.D

Lowe M: Continuing medical education for physicians: Key factors contributing to learning and change. 2007, United States -- Connecticut: University of Connecticut, Ph.D

Yue H: Concept maps as assessment tools in mathematics: Comparison with clinical interviews. 2008, United States -- Texas: The University of Texas at El Paso, MAT

White E: Institutional effectiveness: The integration of program review, strategic planning and budgeting processes in two California community colleges. 2007, Andrews University, Berrien Springs, MI

Grunow JEM: Using concept maps in a professional development program to assess and enhance teachers' understanding of rational number. 1998, United States -- Wisconsin: The University of Wisconsin, Ph.D

Rowe AL: Mental models of physical systems: Examining the relationship between knowing and doing. 1995, Rice University

Kane M, Trochim WMK: Concept mapping for planning and evaluation. 2007, Thousand Oaks, CA, US: Sage Publications, Inc

Chapter   Google Scholar  

Kesby M: Participatory diagramming and the ethical and practical challenges of helping Africans themselves to move HIV work 'beyond epidemiology'. HIV/AIDS in Africa: Beyond Epidemiology. Edited by: Kalipendi E, Craddock S, Oppong J, Ghosh J. 2004, Blackwell, 217-228.

Schreiber DA, Abegg GL: Scoring Student-Generated Concept Maps in Introductory College Chemistry. 1991, The National Association for Research in Science Teaching, 1-19. Annual meeting

Williams CG: Concept Maps as Research Tools in Mathematics. 18 April, 1995. 1995, 1-65.

Varga-Atkins T, O'Brien M: Graphic elicitation as a research technique: reflecting on drawings and diagrams as complementary methods. 2008, 1-22. Ref Type: Report

Emmel N: Participatory Mapping: An innovative sociological method. Toolkit #3. 2008, ESRC National Centre for Research Methods, 1-8. Ref Type: Report

Beyerbach BA: Concept Mapping in Assessing Prospective Teachers' Concept Development. n/a, 1-16. 1986, US Department of Education, Ref Type: Report

Kane M, Trochim WMK: Concept Mapping for Planning and Evaluation. 2007, Thousand Oaks, CA, US: Sage Publications, Inc

Nesbit JC, Adescope O: Learning with concept and knowledge maps: A meta-analysis. Review of Education Research. 2006, 76: 413-448. 10.3102/00346543076003413.

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Muriah J Umoquit, Peggy Tso & Mark J Dobrow

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MJU, MJD, HEDB participated in the conception and design of the study. Data collection, abstraction and analysis was carried out by MJU and PT. MJU and PT prepared the original draft of the manuscript, and all authors reviewed and critically revised the original and subsequent manuscript drafts and approved the final manuscript.

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Umoquit, M.J., Tso, P., Burchett, H.E. et al. A multidisciplinary systematic review of the use of diagrams as a means of collecting data from research subjects: application, benefits and recommendations. BMC Med Res Methodol 11 , 11 (2011). https://doi.org/10.1186/1471-2288-11-11

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A Schematic Research Guide Model: Research Methodology Made Easy

2022, IJASRE

This is not just a flow chart. It is a comprehensive research-tackling-guide-model that directs the researcher where to go, what next to do or achieve at any point on the schematic research diagram. Most researchers get confused on what to do, even at the point of discovering the knowledge and research gap. This work paves the way on how the researcher should begin the research work from the start to the finish point.

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How to develop a graphical framework to chart your research

Graphic representations or frameworks can be powerful tools to explain research processes and outcomes. David Waller explains how researchers can develop effective visual models to chart their work

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Is it time to turn off turnitin, use ai to get your students thinking critically, taming anxiety around public speaking, emotions and learning: what role do emotions play in how and why students learn.

While undertaking a study, researchers can uncover insights, connections and findings that are extremely valuable to anyone likely to read their eventual paper. Thus, it is important for the researcher to clearly present and explain the ideas and potential relationships. One important way of presenting findings and relationships is by developing a graphical conceptual framework.

A graphical conceptual framework is a visual model that assists readers by illustrating how concepts, constructs, themes or processes work. It is an image designed to help the viewer understand how various factors interrelate and affect outcomes, such as a chart, graph or map.

These are commonly used in research to show outcomes but also to create, develop, test, support and criticise various ideas and models. The use of a conceptual framework can vary depending on whether it is being used for qualitative or quantitative research.

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There are many forms that a graphical conceptual framework can take, which can depend on the topic, the type of research or findings, and what can best present the story.

Below are examples of frameworks based on qualitative and quantitative research.

As shown by the table below, in qualitative research the conceptual framework is developed at the end of the study to illustrate the factors or issues presented in the qualitative data. It is designed to assist in theory building and the visual understanding of the exploratory findings. It can also be used to develop a framework in preparation for testing the proposition using quantitative research.

In quantitative research a conceptual framework can be used to synthesise the literature and theoretical concepts at the beginning of the study to present a model that will be tested in the statistical analysis of the research.

It is important to understand that the role of a conceptual framework differs depending on the type of research that is being undertaken.

So how should you go about creating a conceptual framework? After undertaking some studies where I have developed conceptual frameworks, here is a simple model based on “Six Rs”: Review, Reflect, Relationships, Reflect, Review, and Repeat.

Process for developing conceptual frameworks:

Review: literature/themes/theory.

Reflect: what are the main concepts/issues?

Relationships: what are their relationships?

Reflect: does the diagram represent it sufficiently?

Review: check it with theory, colleagues, stakeholders, etc.

Repeat: review and revise it to see if something better occurs.

This is not an easy process. It is important to begin by reviewing what has been presented in previous studies in the literature or in practice. This provides a solid background to the proposed model as it can show how it relates to accepted theoretical concepts or practical examples, and helps make sure that it is grounded in logical sense.

It can start with pen and paper, but after reviewing you should reflect to consider if the proposed framework takes into account the main concepts and issues, and the potential relationships that have been presented on the topic in previous works.

It may take a few versions before you are happy with the final framework, so it is worth continuing to reflect on the model and review its worth by reassessing it to determine if the model is consistent with the literature and theories. It can also be useful to discuss the idea with  colleagues or to present preliminary ideas at a conference or workshop –  be open to changes.

Even after you come up with a potential model it is good to repeat the process to review the framework and be prepared to revise it as this can help in refining the model. Over time you may develop a number of models with each one superseding the previous one.

A concern is that some students hold on to the framework they first thought of and worry that developing or changing it will be seen as a weakness in their research. However, a revised and refined model can be an important factor in justifying the value of the research.

Plenty of possibilities and theoretical topics could be considered to enhance the model. Whether it ultimately supports the theoretical constructs of the research will be dependent on what occurs when it is tested.  As social psychologist, Kurt Lewin, famously said “ There's nothing so practical as good theory ”.

The final result after doing your reviewing and reflecting should be a clear graphical presentation that will help the reader understand what the research is about as well as where it is heading.

It doesn’t need to be complex. A simple diagram or table can clarify the nature of a process and help in its analysis, which can be important for the researcher when communicating to their audience. As the saying goes: “ A picture is worth 1000 words ”. The same goes for a good conceptual framework, when explaining a research process or findings.

David Waller is an associate professor at the University of Technology Sydney .

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Using Visual Diagrams to Communicate Complex Mixed-Methods Research Design Procedures

Mixed methods in public health research in taiwan:, using visual diagrams to communicate complex design procedures, su-i hou, drph, cph, mches, rn, michael d. fetters, md, mph, ma.

Scholars introduce modern mixed methods research (MMR) and its application in public health research in Taiwan. Specifically, they showcase a multi-phased Taiwan Cervical Cancer Screening mixed methods study using visual diagrams to communicate complex design procedures. While some previous researchers have incorporated quantitative and qualitative data in research, here we hope to provide significant clarity to guide those new to the MMR field. We have structured the paper in the following way. First, we provide a brief overview of mixed methods research. Second, we illustrate the compelling need for MMR from a public health perspective using cancer screenings as an example. Third, we introduce the Taiwan Cervical Cancer Screening Program as an exemplar of MMR application and the utility of visual diagrams. Study methodology can be applied to international researchers and scholars from interdisciplinary fields beyond public health.

Keywords: mixed methods research, Taiwan, public health, cervical cancer screening, visual diagram

This is an Accepted Manuscript of an article published by Health Care for Women International on 28/11/2018, available online: https://www.tandfonline.com/doi/full/10.1080/07399332.2018.1516769

Many public health problems are complex. To date, most researchers have attempted to solve these complex problems by using monomethod research approaches. Monomethod research approaches in essence use exclusively quantitative research approaches or exclusively qualitative approaches (Teddlie & Tashakkori, 2009).  Over the past three decades, the mixed methods research paradigm has emerged as a third alternative to quantitative and qualitative research paradigms (Creswell & Clark, 2018). Although modern mixed methods research was established in the late 1980’s and still has a relatively short history, researchers around the globe are embracing mixed methods research (Fetters, 2016).  By integrating both qualitative and quantitative procedures, mixed methods research offers the power of numbers (quantitative) and stories (qualitative) for investigating complex social, behavioral and health sciences (Pluye & Hong, 2013).  Researchers and scholars from public health fields and other social and behavioral science areas can learn the value of modern mixed methods methodology and its development, and how to use visual diagrams to communicate complex mixed methods design procedures.

By definition Mixed Methods Research (MMR) is “a research approach or methodology: (1) focusing on research questions that call for real-life contextual understandings, multi-level perspectives, and cultural influences; (2) employing rigorous quantitative research assessing magnitude and frequency of constructs and rigorous qualitative research exploring the meaning and understanding of constructs; (3) utilizing multiple methods (e.g., intervention trials and in-depth interviews); (4) intentionally integrating or combining these methods to draw on the strengths of each; and (5) framing the investigation within philosophical and theoretical positions” (Creswell, Klassen, Plano Clark, & Clegg Smith, 2011).  A hallmark of mixed methods research is a focus on integration. Fetters and Freshwater propose all mixed methods researchers should take the mixed methods challenge, that is, to consider how to integrate both the qualitative and quantitative data together to achieve a whole greater than the sum of the individual parts. They illustrate this concept numerically as 1 + 1 = 3 (Fetters & Freshwater, 2015). Simply stated, this means the whole (3) is greater than the sum of the respective qualitative (1) and quantitative (1) parts. By integrating, researchers can gain new insights, and more robust conclusions. Ironically, while mixed methods seem strange to many researchers, there are many examples of mixed methods thinking outside of the research world. For example, consumers on their favorite shopping website leave and read reviews for the products they purchased using a five-star quality rating system as well as qualitative comments. By looking at both the star rating (quantitative) and the comments (qualitative), consumers can make informed decisions about purchases.

Mixed Methods Research Internationally and in Taiwan

International literature on mixed methods research.

The modern field of mixed methods research was established in the late 1980’s, and there are over 50 books published on this topic. A number of events signify the growth and vibrancy of the field. The Journal of Mixed Methods Research completed ten years of publication in 2016 (Fetters & Molina-Azorin, 2017), and the International Journal of Multiple Research Approaches re-launched in 2017 after publication from 2007 to 2015. The Mixed Methods International Research Association (MMIRA) convened the first MMIRA conference in Boston, in 2014 (Mertens, et al., 2016). The Japan Society of Mixed Methods Research became the first affiliate of the MMIRA in 2016. In 2017, the first MMIRA Chapter, the Caribbean Chapter of MMIRA was announced. These developments underscore the growth of mixed methods research internationally.

Rationale for Using MMR in Taiwan

As a rapidly aging society, the population of people in Taiwan with cancers and chronic diseases has reached unprecedented levels that continue to grow (Chen, You, Lin, Hsu, & Yang, 2002). Cancer has continued to be the leading cause of death in Taiwan for more than 30 years. Trends of cancer incidence in Taiwan have shown a significant and persistent increase of 1.7% per year from 2002 to 2012 at rates higher than other countries (Chiang, et al., 2016).

While Taiwan has universal health coverage for regular preventive health services including cancer screenings among middle-aged adults age 40 years and older, cancer screening utilization is disappointingly low. Lessons learned from the few existing studies examining selected cancer-screening utilization among community and worksite groups in Taiwan reveal continued and general need to encourage preventive health services utilization (Hou & Chen, 2004; Hou & Chen, 2005; Hou, Fernandez, Baumler, & Parcel, 2002; Hou, Fernandez, Baumler, Parcel, & Chen, 2003; Hou, Hou, & Hou, 2014; Hou & Hou, 2014). Previous cancer screening studies in Taiwan show that only 62% of married women and 31% of single women from a community sample reported a Pap test in the preceding 3 years (Hou, et al., 2003), and less than 30% of a worksite sample had ever had a fecal occult blood test (FOBT) for colorectal cancer screening (Hou & Chen, 2004). Cancer education and screening programs are critical to relieve the cancer burden as many cancers are potentially preventable via modified behavioral lifestyles or early detection via regular screenings. Culturally tailored and innovative screening interventions have been demonstrated effective to significantly encourage more non-adherent women enrolled in the intervention group than in the control group to receive a pap test within 6 months (50% vs. 32%) (Hou, et al., 2002), and encouraged 74% of a midlife workplace sample to return a completed FOBT within 4 weeks (Hou & Chen, 2004; Hou & Chen, 2005).

Implementing effective cancer screening programs and public health services are complex and require interdisciplinary collaboration of many health professionals including nurses, health educators, physicians, social workers, care managers, as well as various community partners. Culturally tailored and innovative screening interventions require deeper understanding of the complex interplay of social, interpersonal, and individual factors influencing the adoption of preventive and screening behaviors. Evaluation and optimization of the delivery of public health programs requires sophisticated research procedures capable of adequately grasping the complexity of the public health enterprise. Mixed methods research which uses qualitative and quantitative data collection procedures, is particularly appropriate for addressing the complex research problems in the field of public health.

Despite the relevance of mixed methods research procedures for investigating complex public health issues, there are limited mixed methods research articles about public health in Taiwan. We conducted a literature search combining the key terms of “mix methods,” “public health,” and “Taiwan” using both the EBSCO host databases and “national library database” in Taiwan with no limitation on time period. This search failed to reveal a single article in the National Library Database in Taiwan when using the terms “mix methods” and “public health”.  We then just used “mix methods” as the key search term. The search revealed five articles from the National Library Database in Taiwan and only one article in the EBSCO host databases conducted in Taiwan using mixed methods.

Using “mixed methods research” as the sole search term may not return some studies that used mixed methods research procedures in cases when the authors did not use the language of mixed methods research (Molina-Azorin & Fetters, 2016). Thus, it is possible that additional studies could be identified if we had used a different search strategy. However, it is unlikely such studies would have used state-of-the-art mixed methods procedures if they did not include mixed methods in the paper. Thus, like Ivankova & Kawamura (2010), we chose “mixed methods” as our key term as we sought studies where the authors were aware of the mixed methods research paradigm and intentionally used “mixed methods” in their study titles or abstract. As a final step, we examined carefully the actual content of all articles identified in the search as “mixed methods studies,” to ensure that all the studies actually met criteria or discussed issues or trends related to mixed methods research.

Based on our literature search in Chinese and English, the few existing mixed methods research articles identified in Taiwan discussed either mixed methodology as a future trend in social and educational research (Hsieh, 2007), or the qualitative-quantitative debates and mixed methods as a new third paradigm (Kuo, 2011). Existing literature in Taiwan mostly pertains to applications in educational research (Tsai & Chauo, 2008; Sung & Pan, 2010). There were two articles identified applying mixed methods in the public health field. One evaluated a health screening program for migrant women to Taiwan (Huang, Mathers, Chia, Shiu, & Kao, 2016), and the other focused on exploring staff understanding and attitudes towards a hospital-balanced scorecard implementation (Ma, Hsu, Huang, Tsai, & Ying, 2011).

Researchers in Taiwan have shown the potential to produce quality mixed methods research. This could be enhanced by better understanding of mixed methods design procedures. Thus, the purpose of this illustration of mixed methods research in public health in Taiwan that follows is to enhance understanding of mixed methods research procedures and to demonstrate the potential for these procedures to be applied much more broadly in public health research. Lessons learned can also be applied to other countries across the world.

An application of mixed methods procedures in public health research

To provide an example of the application of MMR in public health research, here we introduce the Taiwan Cervical Cancer Screening Program, a sophisticated multi-phase mixed methods study, published via a series peer-reviewed articles in Journal of Community Health, Healthcare for Women International, AWHONN Lifelines,Health Promotion Practices, California Journal of Health Promotion, Preventive Medicine, International Journal of Behavioral Medicine, and a book chapter (Hou, et al., 2002; Hou, et al., 2003; Hou & Lessick, 2002; Hou, Fernandez, & Parcel, 2004; Hou & Luh, 2005; Hou, 2005; Hou, 2006a; Hou, 2006b).  This study, “ Love Yourself before You Take Care of Your Family ”, was a hospital-based community outreach program implemented to increase cervical cancer screening among women in Taiwan. This program of research involved a comprehensive process for the development and evaluation of a theory- and evidence-based cancer screening intervention program for Chinese women. This program of mixed methods research involved three major phases: (1) Instrument development and needs assessment (Hou et al, 2003; Hou & Lessick, 2002; Hou & Luh, 2005); (2) Intervention development using a framework called Intervention Mapping (Hou et al, 2004; Hou, 2006a; Hou, 2006b); and (3) Program evaluation using a randomized-controlled trial (Hou et al, 2002; Hou, 2005).  The mixed methods design procedures are illustrated using visual diagrams in order to facilitate communication and understanding [Creswell & Clark, 2018).  The visual diagrams of Phase I to IV of the study help provide a new way to communicate and link the complex mixed methods research design phases, procedures, and products together for readers to better understand the methodological approaches (Figures 1-4).

Phase I Exploring Sequential Design for Instrument Item Development

Phase I explored, developed, and tested study instrument items using an exploratory sequential design. As illustrated in Figure 1, the study explored survey items by reviewing existing literature and theories, and then developing qualitative interview questions. The qualitative data collection involved one-on-one interviews with 14 never-been-tested Chinese women to identify key barriers to cervical cancer screenings. Four screening belief constructs (perceived benefits, barriers, norms, and perceived cancer risk), and screening-related knowledge were identified with corresponding items drafted. This quantitative measurement tool was then preliminarily tested with a sample 125 women in Taiwan. The preliminarily quantitative results showed that measurement scales were reliable, and all four screening beliefs and knowledge were significantly related to cervical cancer screening history ( Figure 1 ).

Phase II Intervention Development Using Intervention Mapping Framework

Phase II was designed with lessons learned from Phase I.  Researchers produced a three-month direct-mail campaign intervention program that was pretested in an 8-person focus group. As illustrated in Figure 2, this “ Love Yourself before You Take Care of Your Family ” cervical cancer screening project was developed using the Intervention Mapping framework (IM), an innovative process of designing theory- and evidence-based interventions. Intervention Mapping involves an inter-connected iterative six-step process to ensure that theory and evidence guiding (a) the identification of psychosocial and environmental determinants related to cancer screening behavior, and (b) the selection of the most appropriate methods and strategies to address the identified determinants ( Figure 2 ).

Phase III Evaluation Study Using Embedded Mixed Methods Research Design

Phase III was a randomized controlled trial (RCT) to evaluate the effectiveness of the intervention developed in Phase II. The primary outcome of the RCT evaluation study was receiving a cervical cancer screening (Pap smear test) after the intervention. A secondary outcome was change knowledge and beliefs concerning cervical cancer screening. Female family members of inpatients who were admitted into a major teaching hospital in Taichung, Taiwan were asked about their cervical cancer screening history. Women who had not had a cervical cancer screening in the past 12 months were identified as non-adherent and thus the were eligible to participate in the randomized controlled intervention trial (total n=424; with 212 women in each group).  As illustrated in Figure 3, this quantitative-dominant evaluation design embedded qualitative data collection (a) before the experiment to gather input on measures, as well as intervention ideas and feasibility; (d) during the experiment to document implementation process and fidelity; and (c) after the experiment to describe the impact ( Figure 3 ).

Results showed women in the intervention group reported a higher rate of receiving cervical cancer screening than women in the comparison group (50% vs. 32%; p=.002).  Baseline data from the randomized controlled intervention trial was further used to confirm the final validated study instrument. Reliabilities showed good internal consistencies for the perceived pros, cons, and susceptibilities scales (alpha ranged from .78 to .87). Factor analysis showed good construct validity revealing concordant patterns with the behavioral constructs used. This validated culturally sensitive and theory-based measurement tool was published with English-Chinese side-by-side to facilitate use by other researchers conducting similar studies (Hou & Luh, 2005). This multi-phase mixed-methods cervical cancer screening program among Chinese women was invited for inclusion in the CDC Chronic Disease Prevention Database to serve as a model to assist researchers and practitioners in planning, implementing, and evaluating health promotion programs in cancer screening ( Figure 4 ).

This Taiwan cervical cancer screening project was published using the concept of staged integration (Fetters, Curry, & Creswell, 2013) via a series of papers from the single multi-phased mixed methods study, including a qualitative paper (Hou & Lessick, 2002), two quantitative papers (Hou, et al., 2003; Hou, 2006a); an instrument development paper (Hou & Luh, 2005), a mixed methods intervention development paper using the Intervention Mapping framework to link all three major phases together (Hou, et al, 2004), two evaluation papers highlighting the project outcomes (Hou, et al., 2002; Hou, 2005), and book chapter used to introduce comprehensively the overall project through use of figures, tables, and intervention material samples (Hou, 2006b).

In this paper, we have introduced this sophisticated multi-phase project that illustrates the complexity, rigor, power, and synergy for publication resulting from using a mixed methods approach. The mixed-methods diagrams have been found to greatly facilitate understanding of various study phases and designs [Phase I, II, III, and the multi-phase figures], and showcase how a series of multiple papers, including a methodological paper, can be published from a program of mixed methods research and integration via the reporting dimension.

As illustrated by the example presented here, mixed methods research offers the power of numbers and stories for investigating complex social and health problems. Understanding the context for using MMR in Taiwan from a public health perspective underscores the opportunity for applications of mixed methods in public health research. While a concise overview of mixed methods research, this paper illustrates a sophisticated mixed methods cervical cancer screening program of research based in Taiwan as an exemplar of MMR application. Visual diagrams greatly facilitate communication of complex mixed methods design procedures. As illustrated, multiple papers can be published from a mixed method program of research, and this work illustrates mixed methods research integration through the reporting dimension.  The methodology discussed can be applied to interdisciplinary fields of research and across the world.

• Ethical approval: “All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.”  
• Informed consent: “Informed consent was obtained from all individual participants included in the study.”
• Disclosure of potential conflicts of interest: “The authors declare that they have no conflict of interest.”

Chen, C.-J., You, S.-L., Lin, L.-H., Hsu, W.-L. and Yang, Y.-W. (2002) Cancer epidemiology and control in Taiwan: a brief review. Japanese journal of clinical oncology , 32 , S66-S81.

Chiang, C.-J., Lo, W.-C., Yang, Y.-W., You, S.-L., Chen, C.-J., & Lai, M.-S. (2016) Incidence and survival of adult cancer patients in Taiwan, 2002–2012. Journal of the Formosan Medical Association , 115 ,1076-1088

Creswell, J., & Clark V.L. (2018). Designing and conducting mixed methods research . (3rded.) Sage publications, Inc.  ISBN: 978-1-4833-4437-9

Creswell, J.W., Klassen, A.C., Plano Clark, V.L., & Smith, K.C. (2011). Best practices for mixed methods research in the health sciences. Bethesda, MD: National Institutes of Health .

Fetters M.D. “Haven’t we always been doing mixed methods research?”: Lessons learned from the development of the horseless carriage. Journal of Mixed Methods Research, 10 (1), 3-11, 2016.

Fetters M.D., Curry L.A., & Creswell J.W. (2013). Achieving integration in mixed methods designs – principles and practices. Health Service Research, 48(6 Pt 2), 2134-56.

Fetters M.D., & Freshwater D. (2015). The 1 + 1 = 3 Integration Challenge. Journal of Mixed Methods Research, 9 (2), 115-7.

Fetters MD and Molina-Azorin JF. (2017). The Journal of Mixed Methods Research Starts a New Decade: The Integration Trilogy and Its Dimensions. Journal of Mixed Methods Research . 11(3).

Hou S.-I.  (2005). Stage of adoption and impact of direct-mail communications with and without phone intervention on Chinese women’s cervical smear screening behavior. Preventive Medicine, 41 , 49-756.

Hou, S.-I.(2006a).  Perceived spousal support and beliefs towards cervical smear screening among Chinese women. California Journal of Health Promotion, 4 (3), 157-164.

Hou, S.-I. (2006b). Using Intervention Mapping in Program Development to Promote Cervical Cancer Screening among Chinese Women – From Needs Assessment, Intervention Development, to Program Evaluation.  In George Rolland (Ed.), New Research on Cervical Cancer .  (Chap 1. pp.1-46).  Hauppauge, NY: Nova Science Publishers, Inc. (ISBN 1-60021-300-6).

Hou, S.-I., & Chen, P.-H. (2004) Home-administered fecal occult blood test for colorectal cancer screening among worksites in Taiwan. Preventive Medicine , 38 , 78-84.

Hou, S.-I., & Chen, P.-H. (2005) Cancer screening beliefs and reactions to an innovative colorectal cancer screening kit among Chinese worksite population. Methods of Information in Medicine , 44 , 315-318.

Hou, S.-I., Fernandez, M. E., Baumler, E. & Parcel, G. S. (2002). Effectiveness of an intervention to increase Pap test screening among Chinese women in Taiwan. Journal of community health , 27 , 277-290.

Hou, S.-I., Fernandez, M., Baumler, E., Parcel, G, & Chen P. (2003).Correlates of cervical cancer screening among women in Taiwan.  Health Care for Women International, 24 (5), 384-398 .

Hou, S.-I., Fernandez, M., & Parcel, G. (2004). Development of a cervical cancer educational program for Chinese women using Intervention Mapping. Health Promotion Practice, 5 (1), 80-87 .

Hou, S.-I., & Hou, P.-H. (2014) Developing and Validating a PHSU Belief Inventory (PHSU-BI) among Chinese Middle-aged White-and Blue-collar Workers. International Journal of Health, Wellness and Society , 4 , 13-20.

Hou, S.-I., Hou., P.-H, & Hou., H.-S. (2014) The impact of a colorectal cancers worksite screening intervention on knowledge, screening beliefs, and uptakes among middle- and older-age employees in Taiwan. Journal of Cancer Education , 29 , S12-13.

Hou, S.-I., &Lessick, M. (2002). Cervical cancer screening among Chinese women: Exploring the benefits and barriers of providing care. AWHONN Lifelines, 6 (4), 349-354.

Hou, S.-I., & Luh, W. (2005).  Psychometric properties of the Cervical Smear Belief Inventory (CSBI) for Chinese women.  International Journal of Behavior Medicine, 12 (3),180-191 .

Huang, Y.-C., Mathers, N. J., Chia, S.-L., Shiu, M.-N., & Kao, S.-C. (2016). An evaluation of a screening programme for immigrant women to Taiwan. Family Medicine and Community Health, 4 (2), 5-15.

Hsieh C.W. (2007). Educational Research Paradigm of Future: The Introduction of Mixed Methodology. Ping-Tong Education University Report, 175-194. [In Chinese: English abstract]

Ivankova N, & Kawamura Y. (2010). Emerging trends in the utilization of integrated designs in the social, behavior, and health sciences. In: Tashakkori A, Teddlie C eds, Handbook of mixed methods in social & behavioral research. 2th ed. Thousand Oaks, CA:Sage, 581-611.

Kuo C.Y. (2011). Mixed research and the qualitative-quantitative debat. Soochow Journal of Political Science, 29 (1), 1-64. [In Chinese: English abstract]

Ma C.C., Hsu M.H., Huang S.K., Tsai Y.T., & Ying J.C. (2011). Using mixed methods to explore staff understanding, attitudes and problems in the iImplementation of balanced scorecard. Journal of Medical Management(Taiwan), 12 (2), 98-113.[In Chinese: English abstract]

Mertens, D., Bazeley, P., Bowleg, L., Fielding, N., Maxwell, J., Molina-Azorin, J.F., & Niglas, K. (2016). The future of mixed methods: A five year projection to 2020.  Retrieved from: https://mmira.wildapricot.org/resources/Documents/MMIRA%20task%20force%20report%20Jan2016%20final.pdf

Molina-Azorin J.F., & Fetters M.D. (2016). Mixed methods research prevalence studies: Field-specific studies on the state of the art of mixed methods research. Journal of Mixed Methods Research, 10 (2):123-128.

Pluye, P., & Hong, Q.N. (2013). Combining the power of stories and the power of numbers: Mixed methods research and mixed studies reviews. Annual Review of Public Health, 35 , 29-45.  https://doi.org/10.1146/annurev-publhealth-032013-182440

Sung Y.T., & Pan P.Y.(2010).Applications of mixed methods research in educational studies. Jouranl of Educational Research, 55(4), 97-130. [In Chinese: English abstract]

Teddlie C., & Tashakkori, A. (2009). Foundations of Mixed Methods Research-Integrating quantitative and qualitative approaches in the Social and Behavioral Sciences . Sage Publications, Thousand Oaks, CA.

Tsai H.M., & Chauo C.W. (2008). The paradigmatic analysis of adult education research and discussing of the tendency of adult education research in Taiwan. Humanity of Social Science , 159-177. [In Chinese: English abstract]

Mixed-Methods Evaluation Copyright © 2020 by Su-I Hou is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License , except where otherwise noted.

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